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Qualcomm Innovation Fellowship Europe Rewards Excellent Research in AI and Cybersecurity
SAN DIEGO, California, July 28 -- Qualcomm Technologies, a subsidiary of Qualcomm, issued the following news release on July 27, 2026:
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Qualcomm Innovation Fellowship Europe Rewards Excellent Research in AI and Cybersecurity
Each Winner Receives Mentorship and $40,000 in Research Funding
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Qualcomm Technologies, Inc. today unveiled the latest recipients of the Qualcomm Innovation Fellowship (QIF) Europe, an award now marking its 17th edition. This year's five fellows are Mar Gonzalez I Catala (University of Cambridge), Jiajun He (University of Cambridge), Abhinandan Pal (University of ... Show Full Article SAN DIEGO, California, July 28 -- Qualcomm Technologies, a subsidiary of Qualcomm, issued the following news release on July 27, 2026: * * * Qualcomm Innovation Fellowship Europe Rewards Excellent Research in AI and Cybersecurity Each Winner Receives Mentorship and $40,000 in Research Funding - Qualcomm Technologies, Inc. today unveiled the latest recipients of the Qualcomm Innovation Fellowship (QIF) Europe, an award now marking its 17th edition. This year's five fellows are Mar Gonzalez I Catala (University of Cambridge), Jiajun He (University of Cambridge), Abhinandan Pal (University ofBirmingham), Naila Sebastian Esandi (INRIA / ENSAE Paris), and Christopher Wewer (Max Planck Institute for Informatics).
Held each year across Europe, India, and the United States, QIF exists to spotlight, celebrate, and nurture the engineering PhD students producing the field's boldest work. In Europe, the fellowship turns its focus to promising early-career talent in artificial intelligence and cybersecurity, giving every recipient a $40,000 award alongside one-on-one mentorship from the Qualcomm Technologies research team.
"Submissions climbed to an all-time high this year--close to 50 percent above last year's total--which says a great deal about how fast machine learningAI is moving, and how vital it is to keep our rapidly evolving hardware and software secure," said Michael Hofmann, Senior Director of Engineering at Qualcomm Technologies Netherlands B.V. "What stood out was the sheer range of the proposals, stretching from multimodal generation, trustworthy agents, world models, robotics, and generative AI safety to hardware verification, secure systems, privacy, communications, edge AI, and machine learning for scientific discovery. We're honored to continue mentoring each of the winners as their research unfolds."
This year's five fellows emerged from a shortlist of eighteen finalists, drawn from PhD programs at CISPA, ETH Zurich, INRIA, KU Leuven, Max Planck Institute for Informatics, Max Planck Institute for Intelligent Systems, Max Planck Institute for Security and Privacy, Technical University of Munich, University of Amsterdam, University of Birmingham, University of Cambridge, University of Oxford, and University of Tubingen.
After careful review, the following five fellows were selected for their outstanding proposals:
"A Geometric Theory of Autoregressive Reasoning" - Mar Gonzalez I Catala (University of Cambridge)
Reasoning models increasingly expose chain-of-thought traces that make parts of their problem-solving process observable, yet the structure and significance of these traces remain poorly understood. Recent work suggests that entropy dynamics within reasoning traces correlate with correctness and can serve as useful diagnostic or intervention signals. This project asks whether such signals reflect a deeper structure: an underlying geometry of reasoning trajectories that could explain both when models become uncertain and how they converge, stabilize, derail, or recover. To make this hypothesis operational, we propose to model autoregressive reasoning as a stochastic dynamical system over latent reasoning states, with chain-of-thought traces interpreted as trajectories that terminate in answer attractors. From this perspective, reasoning quality can be characterized not only by the final answer produced, but also by the geometry of the trajectory that leads to it. The framework further suggests new forms of intervention: training objectives that encourage desirable trajectory geometries, and inference-time methods that redirect trajectories converging to incorrect answers.
"Robust Diffusion Model Control for Multiple-Constraint Inverse Problems with Replica Exchange" - Jiajun He (University of Cambridge)
Diffusion models are powerful generative priors across images, molecules, proteins, and scientific domains, but real applications increasingly require test-time control under measurements, preferences, and multiple evolving constraints. Existing methods such as guidance, sequential Monte Carlo, and search can become biased, tuning-sensitive, or prone to diversity collapse under strong constraints. This proposal develops a replica-exchange framework for robust diffusion model control. The first key innovation is path-space exchange: by exchanging and reweighting trajectories, the method avoids unreliable marginal-density approximations and remains accurate under imperfect learned or non-diffusive dynamics. The second is online adaptation: the method can diagnose poor mixing, refine the replica ladder, improve proposal dynamics, and continue inference as constraints harden or evolve. Together, these advances aim to deliver a stable, diverse, adaptive, and plug-and-play control procedure, with wide applications in generation, simulation, and scientific discovery.
"Neural Model Checking for Hardware Verification" - Abhinandan Pal (University of Birmingham)
Before hardware is manufactured, engineers must show that unwanted behaviour never occurs, and that required behaviour eventually does. This task is becoming harder as circuits grow more complex, and AI tools begin to generate hardware-design code more rapidly. My research develops Neural Model Checking (NMC), which learns a small neural network from sample executions as a candidate correctness proof. A mathematical solver then checks this proof against every possible behaviour of the circuit. If the solver does not find a violation, it proves the required property rather than merely testing selected examples. On SystemVerilog benchmarks, NMC is substantially faster than leading fully automated verification tools. This fellowship will move NMC from academic promise to industry-relevant hardware verification. The project focuses on building a test suite of realistic hardware designs and correctness requirements, identifying the tasks that defeat existing automated tools, and extending the theory and implementation of NMC to handle real-world designs. The project will deliver a reproducible evaluation pipeline and measure how far automated, solver-checked proofs can scale in practical hardware development. Its goal is to automate verification tasks that currently require extensive manual proof effort or rely on testing that may miss critical corner cases.
"A Theoretical Framework for Zero-Shot Reinforcement Learning" - Naila Sebastian Esandi (INRIA / ENSAE Paris)
While Reinforcement Learning (RL) has successfully addressed complex control problems without the need for high-fidelity world models, a significant bottleneck remains: the requirement to solve a planning problem for each objective independently. This redundancy is computationally unfeasible for endpoint devices, such as autonomous vehicles, surgical robots, or mobile phones. Zero-Shot RL (ZSRL) has emerged as a candidate paradigm to satisfy these hardware constraints; however, its progress is currently restricted by a lack of rigorous theoretical foundations and unified evaluation methods. This project aims to bridge this gap by establishing a formal framework for ZSRL and developing a new class of theoretically grounded, efficient algorithms.
"Towards Scene State Tokenization for World Models" - Christopher Wewer (Max Planck Institute for Informatics)
Recent models like Genie 3 or LingBot-World are impressive video generators, but they fall short as world models for three reasons. Since they operate on video frames, (1) the same environment is not guaranteed to behave the same way under two different actions, (2) long-horizon simulation forces expensive history caching, and (3) inference cost is fixed regardless of how complex the scene actually is. In this project, I argue that the main bottleneck is the representation, not the architecture. Videos are only observations of a world, not the world itself. I propose to learn compact latent scene states that describe the physical configurations of environments, including geometry, object identity, and the attributes needed to predict what happens next. On top of these states, I introduce state-space world models that update a single world state over time, rather than accumulating a growing history of video frames. Observations are then decoded from these states. I will outline how such latent states can be learned: first by training an encoder-decoder on complete synthetic scenes, then by treating the encoder as a conditional generative model that infers full states from partial observations, and finally by bridging the gap to real video data. This builds directly on my prior work on compressed 3D scene tokens (SceneTok), generative 3D reconstruction, and spatial reasoning with diffusion models.
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About Qualcomm
Qualcomm is a global computing leader at the center of the AI era, enabling intelligence to scale from the most personal devices to large scale infrastructure. Building on more than four decades of innovation, we develop platforms and solutions that bring together advanced AI, high performance, low power computing and industry leading connectivity--powering products and services used around the world. At Qualcomm, we are engineering human progress.
Qualcomm Incorporated includes our licensing business, QTL, and the vast majority of our patent portfolio. Qualcomm Technologies, Inc., a subsidiary of Qualcomm Incorporated, operates, along with its subsidiaries, substantially all of our engineering and research and development functions and substantially all of our products and services businesses, including our QCT semiconductor business. Snapdragon and Qualcomm branded products are products of Qualcomm Technologies, Inc. and/or its subsidiaries. Qualcomm patents are licensed by Qualcomm Incorporated. Qualcomm, Snapdragon, Qualcomm Dragonwing and Qualcomm Dragonfly are trademarks or registered trademarks of Qualcomm Incorporated.
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Original text here: https://www.qualcomm.com/news/releases/2026/07/qualcomm-innovation-fellowship-europe-rewards-excellent-research
[Category: BizElectronic Products]
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Qualcomm Innovation Fellowship Europe Rewards Excellent Research in AI and Cybersecurity
Each Winner Receives Mentorship and $40,000 in Research Funding
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Qualcomm Technologies, Inc. today unveiled the latest recipients of the Qualcomm Innovation Fellowship (QIF) Europe, an award now marking its 17th edition. This year's five fellows are Mar Gonzalez I Catala (University of Cambridge), Jiajun He (University of Cambridge), Abhinandan Pal (University of ... Show Full Article SAN DIEGO, California, July 28 -- Qualcomm Technologies, a subsidiary of Qualcomm, issued the following news release on July 27, 2026: * * * Qualcomm Innovation Fellowship Europe Rewards Excellent Research in AI and Cybersecurity Each Winner Receives Mentorship and $40,000 in Research Funding - Qualcomm Technologies, Inc. today unveiled the latest recipients of the Qualcomm Innovation Fellowship (QIF) Europe, an award now marking its 17th edition. This year's five fellows are Mar Gonzalez I Catala (University of Cambridge), Jiajun He (University of Cambridge), Abhinandan Pal (University ofBirmingham), Naila Sebastian Esandi (INRIA / ENSAE Paris), and Christopher Wewer (Max Planck Institute for Informatics).
Held each year across Europe, India, and the United States, QIF exists to spotlight, celebrate, and nurture the engineering PhD students producing the field's boldest work. In Europe, the fellowship turns its focus to promising early-career talent in artificial intelligence and cybersecurity, giving every recipient a $40,000 award alongside one-on-one mentorship from the Qualcomm Technologies research team.
"Submissions climbed to an all-time high this year--close to 50 percent above last year's total--which says a great deal about how fast machine learningAI is moving, and how vital it is to keep our rapidly evolving hardware and software secure," said Michael Hofmann, Senior Director of Engineering at Qualcomm Technologies Netherlands B.V. "What stood out was the sheer range of the proposals, stretching from multimodal generation, trustworthy agents, world models, robotics, and generative AI safety to hardware verification, secure systems, privacy, communications, edge AI, and machine learning for scientific discovery. We're honored to continue mentoring each of the winners as their research unfolds."
This year's five fellows emerged from a shortlist of eighteen finalists, drawn from PhD programs at CISPA, ETH Zurich, INRIA, KU Leuven, Max Planck Institute for Informatics, Max Planck Institute for Intelligent Systems, Max Planck Institute for Security and Privacy, Technical University of Munich, University of Amsterdam, University of Birmingham, University of Cambridge, University of Oxford, and University of Tubingen.
After careful review, the following five fellows were selected for their outstanding proposals:
"A Geometric Theory of Autoregressive Reasoning" - Mar Gonzalez I Catala (University of Cambridge)
Reasoning models increasingly expose chain-of-thought traces that make parts of their problem-solving process observable, yet the structure and significance of these traces remain poorly understood. Recent work suggests that entropy dynamics within reasoning traces correlate with correctness and can serve as useful diagnostic or intervention signals. This project asks whether such signals reflect a deeper structure: an underlying geometry of reasoning trajectories that could explain both when models become uncertain and how they converge, stabilize, derail, or recover. To make this hypothesis operational, we propose to model autoregressive reasoning as a stochastic dynamical system over latent reasoning states, with chain-of-thought traces interpreted as trajectories that terminate in answer attractors. From this perspective, reasoning quality can be characterized not only by the final answer produced, but also by the geometry of the trajectory that leads to it. The framework further suggests new forms of intervention: training objectives that encourage desirable trajectory geometries, and inference-time methods that redirect trajectories converging to incorrect answers.
"Robust Diffusion Model Control for Multiple-Constraint Inverse Problems with Replica Exchange" - Jiajun He (University of Cambridge)
Diffusion models are powerful generative priors across images, molecules, proteins, and scientific domains, but real applications increasingly require test-time control under measurements, preferences, and multiple evolving constraints. Existing methods such as guidance, sequential Monte Carlo, and search can become biased, tuning-sensitive, or prone to diversity collapse under strong constraints. This proposal develops a replica-exchange framework for robust diffusion model control. The first key innovation is path-space exchange: by exchanging and reweighting trajectories, the method avoids unreliable marginal-density approximations and remains accurate under imperfect learned or non-diffusive dynamics. The second is online adaptation: the method can diagnose poor mixing, refine the replica ladder, improve proposal dynamics, and continue inference as constraints harden or evolve. Together, these advances aim to deliver a stable, diverse, adaptive, and plug-and-play control procedure, with wide applications in generation, simulation, and scientific discovery.
"Neural Model Checking for Hardware Verification" - Abhinandan Pal (University of Birmingham)
Before hardware is manufactured, engineers must show that unwanted behaviour never occurs, and that required behaviour eventually does. This task is becoming harder as circuits grow more complex, and AI tools begin to generate hardware-design code more rapidly. My research develops Neural Model Checking (NMC), which learns a small neural network from sample executions as a candidate correctness proof. A mathematical solver then checks this proof against every possible behaviour of the circuit. If the solver does not find a violation, it proves the required property rather than merely testing selected examples. On SystemVerilog benchmarks, NMC is substantially faster than leading fully automated verification tools. This fellowship will move NMC from academic promise to industry-relevant hardware verification. The project focuses on building a test suite of realistic hardware designs and correctness requirements, identifying the tasks that defeat existing automated tools, and extending the theory and implementation of NMC to handle real-world designs. The project will deliver a reproducible evaluation pipeline and measure how far automated, solver-checked proofs can scale in practical hardware development. Its goal is to automate verification tasks that currently require extensive manual proof effort or rely on testing that may miss critical corner cases.
"A Theoretical Framework for Zero-Shot Reinforcement Learning" - Naila Sebastian Esandi (INRIA / ENSAE Paris)
While Reinforcement Learning (RL) has successfully addressed complex control problems without the need for high-fidelity world models, a significant bottleneck remains: the requirement to solve a planning problem for each objective independently. This redundancy is computationally unfeasible for endpoint devices, such as autonomous vehicles, surgical robots, or mobile phones. Zero-Shot RL (ZSRL) has emerged as a candidate paradigm to satisfy these hardware constraints; however, its progress is currently restricted by a lack of rigorous theoretical foundations and unified evaluation methods. This project aims to bridge this gap by establishing a formal framework for ZSRL and developing a new class of theoretically grounded, efficient algorithms.
"Towards Scene State Tokenization for World Models" - Christopher Wewer (Max Planck Institute for Informatics)
Recent models like Genie 3 or LingBot-World are impressive video generators, but they fall short as world models for three reasons. Since they operate on video frames, (1) the same environment is not guaranteed to behave the same way under two different actions, (2) long-horizon simulation forces expensive history caching, and (3) inference cost is fixed regardless of how complex the scene actually is. In this project, I argue that the main bottleneck is the representation, not the architecture. Videos are only observations of a world, not the world itself. I propose to learn compact latent scene states that describe the physical configurations of environments, including geometry, object identity, and the attributes needed to predict what happens next. On top of these states, I introduce state-space world models that update a single world state over time, rather than accumulating a growing history of video frames. Observations are then decoded from these states. I will outline how such latent states can be learned: first by training an encoder-decoder on complete synthetic scenes, then by treating the encoder as a conditional generative model that infers full states from partial observations, and finally by bridging the gap to real video data. This builds directly on my prior work on compressed 3D scene tokens (SceneTok), generative 3D reconstruction, and spatial reasoning with diffusion models.
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About Qualcomm
Qualcomm is a global computing leader at the center of the AI era, enabling intelligence to scale from the most personal devices to large scale infrastructure. Building on more than four decades of innovation, we develop platforms and solutions that bring together advanced AI, high performance, low power computing and industry leading connectivity--powering products and services used around the world. At Qualcomm, we are engineering human progress.
Qualcomm Incorporated includes our licensing business, QTL, and the vast majority of our patent portfolio. Qualcomm Technologies, Inc., a subsidiary of Qualcomm Incorporated, operates, along with its subsidiaries, substantially all of our engineering and research and development functions and substantially all of our products and services businesses, including our QCT semiconductor business. Snapdragon and Qualcomm branded products are products of Qualcomm Technologies, Inc. and/or its subsidiaries. Qualcomm patents are licensed by Qualcomm Incorporated. Qualcomm, Snapdragon, Qualcomm Dragonwing and Qualcomm Dragonfly are trademarks or registered trademarks of Qualcomm Incorporated.
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Original text here: https://www.qualcomm.com/news/releases/2026/07/qualcomm-innovation-fellowship-europe-rewards-excellent-research
[Category: BizElectronic Products]
Newmark Facilitates Sale and Financing of 140-Unit Multifamily Community in Charlotte, North Carolina
NEW YORK, July 28 -- Newmark Group, a commercial real estate company that says they offer comprehensive suite of services and products, posted the following news release:
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Newmark Facilitates Sale and Financing of 140-Unit Multifamily Community in Charlotte, North Carolina
Newmark announces the Company has arranged the $27.8 million sale of and $15.9 million in acquisition financing for Reserve at Waterford Lakes, a 140-unit garden-style multifamily community located at 8725 Kody Marie Court in Charlotte, North Carolina.
Newmark Senior Managing Director Jason Kon, Vice Chairmen Dean Smith, ... Show Full Article NEW YORK, July 28 -- Newmark Group, a commercial real estate company that says they offer comprehensive suite of services and products, posted the following news release: * * * Newmark Facilitates Sale and Financing of 140-Unit Multifamily Community in Charlotte, North Carolina Newmark announces the Company has arranged the $27.8 million sale of and $15.9 million in acquisition financing for Reserve at Waterford Lakes, a 140-unit garden-style multifamily community located at 8725 Kody Marie Court in Charlotte, North Carolina. Newmark Senior Managing Director Jason Kon, Vice Chairmen Dean Smith,John Heimburger and Sean Wood, Senior Managing Director John Munroe and Managing Director Brenna Campbell represented the seller, Eller Capital Partners, in the sale transaction. Executive Managing Director Josh Davis and Director Patrick Breed secured the financing through Freddie Mac on behalf of the buyer, Ascent Housing.
The acquisition marks the 10th multifamily asset Newmark has facilitated for Ascent Housing, a mission-driven owner focused on preserving naturally occurring affordable housing throughout Mecklenburg County. As part of its ownership strategy, Ascent Housing is committed to maintaining affordability while investing in resident-focused programming, including on-site collaborations that support financial empowerment, education, health and wellness initiatives.
"We are thrilled to have delivered a successful outcome for our client while identifying a buyer whose long-term vision aligns with the property's role in the community," said Kon. "It's increasingly rare to find buyers committed to preserving affordable housing in highly desirable locations while also investing in programs and services that create meaningful opportunities for residents. Ascent Housing's mission makes it a truly unique owner in today's market."
Built in 2008, Reserve at Waterford Lakes offers one- and two-bedroom apartment homes featuring modern kitchens with black or stainless steel appliances, glass cooktops, nine-foot ceilings and crown molding. Community amenities include a swimming pool, fitness center, resident lounge with games, business center and outdoor picnic and grilling areas.
The property is situated in South Charlotte, just minutes from the Sharon Road West Station on the LYNX Blue Line, providing convenient access to many of the region's largest employment centers, including South End, SouthPark, Ballantyne and the Quail Hollow area. Residents also benefit from nearby shopping, dining and entertainment destinations such as Carolina Pavilion, Carolina Place, SouthPark Mall, Carowinds and Topgolf, as well as convenient access to Interstates 485 and 77.
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About Newmark
Newmark Group, Inc. (Nasdaq: NMRK), together with its subsidiaries ("Newmark"), is a world leader in commercial real estate, seamlessly powering every phase of the property life cycle. Newmark's comprehensive suite of services and products is uniquely tailored to each client, from owners to occupiers, investors to founders, and startups to blue-chip companies. Combining the platform's global reach with market intelligence in both established and emerging property markets, Newmark provides superior service to clients across the industry spectrum. For the twelve months ended March 31, 2026, Newmark generated revenues of more than $3.4 billion. As of March 31, 2026, Newmark and its business partners together operated from over 185 offices with more than 9,600 professionals across four continents. To learn more, visit nmrk.com or follow @newmark.
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Discussion of Forward-Looking Statements about Newmark
Statements in this document regarding Newmark that are not historical facts are "forward-looking statements" that involve risks and uncertainties, which could cause actual results to differ from those contained in the forward-looking statements. These include statements about the Company's business, results, financial position, liquidity, and outlook, which may constitute forward-looking statements and are subject to the risk that the actual impact may differ, possibly materially, from what is currently expected. Except as required by law, Newmark undertakes no obligation to update any forward-looking statements. For a discussion of additional risks and uncertainties, which could cause actual results to differ from those contained in the forward-looking statements, see Newmark's Securities and Exchange Commission filings, including, but not limited to, the risk factors and Special Note on Forward-Looking Information set forth in these filings and any updates to such risk factors and Special Note on Forward-Looking Information contained in subsequent reports on Form 10-K, Form 10-Q or Form 8-K.
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Original text here:
[Category: BizReal Estate]
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Newmark Facilitates Sale and Financing of 140-Unit Multifamily Community in Charlotte, North Carolina
Newmark announces the Company has arranged the $27.8 million sale of and $15.9 million in acquisition financing for Reserve at Waterford Lakes, a 140-unit garden-style multifamily community located at 8725 Kody Marie Court in Charlotte, North Carolina.
Newmark Senior Managing Director Jason Kon, Vice Chairmen Dean Smith, ... Show Full Article NEW YORK, July 28 -- Newmark Group, a commercial real estate company that says they offer comprehensive suite of services and products, posted the following news release: * * * Newmark Facilitates Sale and Financing of 140-Unit Multifamily Community in Charlotte, North Carolina Newmark announces the Company has arranged the $27.8 million sale of and $15.9 million in acquisition financing for Reserve at Waterford Lakes, a 140-unit garden-style multifamily community located at 8725 Kody Marie Court in Charlotte, North Carolina. Newmark Senior Managing Director Jason Kon, Vice Chairmen Dean Smith,John Heimburger and Sean Wood, Senior Managing Director John Munroe and Managing Director Brenna Campbell represented the seller, Eller Capital Partners, in the sale transaction. Executive Managing Director Josh Davis and Director Patrick Breed secured the financing through Freddie Mac on behalf of the buyer, Ascent Housing.
The acquisition marks the 10th multifamily asset Newmark has facilitated for Ascent Housing, a mission-driven owner focused on preserving naturally occurring affordable housing throughout Mecklenburg County. As part of its ownership strategy, Ascent Housing is committed to maintaining affordability while investing in resident-focused programming, including on-site collaborations that support financial empowerment, education, health and wellness initiatives.
"We are thrilled to have delivered a successful outcome for our client while identifying a buyer whose long-term vision aligns with the property's role in the community," said Kon. "It's increasingly rare to find buyers committed to preserving affordable housing in highly desirable locations while also investing in programs and services that create meaningful opportunities for residents. Ascent Housing's mission makes it a truly unique owner in today's market."
Built in 2008, Reserve at Waterford Lakes offers one- and two-bedroom apartment homes featuring modern kitchens with black or stainless steel appliances, glass cooktops, nine-foot ceilings and crown molding. Community amenities include a swimming pool, fitness center, resident lounge with games, business center and outdoor picnic and grilling areas.
The property is situated in South Charlotte, just minutes from the Sharon Road West Station on the LYNX Blue Line, providing convenient access to many of the region's largest employment centers, including South End, SouthPark, Ballantyne and the Quail Hollow area. Residents also benefit from nearby shopping, dining and entertainment destinations such as Carolina Pavilion, Carolina Place, SouthPark Mall, Carowinds and Topgolf, as well as convenient access to Interstates 485 and 77.
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About Newmark
Newmark Group, Inc. (Nasdaq: NMRK), together with its subsidiaries ("Newmark"), is a world leader in commercial real estate, seamlessly powering every phase of the property life cycle. Newmark's comprehensive suite of services and products is uniquely tailored to each client, from owners to occupiers, investors to founders, and startups to blue-chip companies. Combining the platform's global reach with market intelligence in both established and emerging property markets, Newmark provides superior service to clients across the industry spectrum. For the twelve months ended March 31, 2026, Newmark generated revenues of more than $3.4 billion. As of March 31, 2026, Newmark and its business partners together operated from over 185 offices with more than 9,600 professionals across four continents. To learn more, visit nmrk.com or follow @newmark.
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Discussion of Forward-Looking Statements about Newmark
Statements in this document regarding Newmark that are not historical facts are "forward-looking statements" that involve risks and uncertainties, which could cause actual results to differ from those contained in the forward-looking statements. These include statements about the Company's business, results, financial position, liquidity, and outlook, which may constitute forward-looking statements and are subject to the risk that the actual impact may differ, possibly materially, from what is currently expected. Except as required by law, Newmark undertakes no obligation to update any forward-looking statements. For a discussion of additional risks and uncertainties, which could cause actual results to differ from those contained in the forward-looking statements, see Newmark's Securities and Exchange Commission filings, including, but not limited to, the risk factors and Special Note on Forward-Looking Information set forth in these filings and any updates to such risk factors and Special Note on Forward-Looking Information contained in subsequent reports on Form 10-K, Form 10-Q or Form 8-K.
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Original text here:
[Category: BizReal Estate]
Richmond Law Firm McGuireWoods Represents John Laing Group in Financing Acquisition of Connecticut Utility
RICHMOND, Virginia, July 28 -- McGuireWoods, a law firm, issued the following news release:
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McGuireWoods Represents John Laing Group in Financing Acquisition of Connecticut Utility
McGuireWoods advised John Laing Group, a leading international investor and active manager of core infrastructure assets, on its financing for the acquisition of a Connecticut water system serving 735,000 people in 60 municipalities.
John Laing supported Aquarion Water Authority (AWA), which was formed by Connecticut lawmakers in 2024, in its purchase of the Aquarion Company from Eversource. John Laing's role ... Show Full Article RICHMOND, Virginia, July 28 -- McGuireWoods, a law firm, issued the following news release: * * * McGuireWoods Represents John Laing Group in Financing Acquisition of Connecticut Utility McGuireWoods advised John Laing Group, a leading international investor and active manager of core infrastructure assets, on its financing for the acquisition of a Connecticut water system serving 735,000 people in 60 municipalities. John Laing supported Aquarion Water Authority (AWA), which was formed by Connecticut lawmakers in 2024, in its purchase of the Aquarion Company from Eversource. John Laing's roleis part of a broader financing solution, which includes a public bond issuance led by Bank of America and included Barclays as an additional underwriter.
McGuireWoods partners Jake Spilman and Douglas Lamb led the deal team. Other key members of the deal team included counsel Clinton Randolph and Ryan Thompson, partner Robert Kaplan and associate Johnny Mac Yates.
"We were proud to assist John Laing with this transaction and for our continued partnership with John Laing," Spilman said. "The deal reflects John Laing's commitment to providing innovative financing to support essential infrastructure."
McGuireWoods' full-service team of lawyers work cohesively with colleagues in all of the firm's groups to deliver end-to-end deal support tailored to each transaction.
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URL: John Laing Group
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Original text here: https://www.mcguirewoods.com/news/press-releases/2026/7/mcguirewoods-represents-john-laing-group-in-financing-acquisition-of-connecticut-utility/
[Category: BizLaw/Legal]
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McGuireWoods Represents John Laing Group in Financing Acquisition of Connecticut Utility
McGuireWoods advised John Laing Group, a leading international investor and active manager of core infrastructure assets, on its financing for the acquisition of a Connecticut water system serving 735,000 people in 60 municipalities.
John Laing supported Aquarion Water Authority (AWA), which was formed by Connecticut lawmakers in 2024, in its purchase of the Aquarion Company from Eversource. John Laing's role ... Show Full Article RICHMOND, Virginia, July 28 -- McGuireWoods, a law firm, issued the following news release: * * * McGuireWoods Represents John Laing Group in Financing Acquisition of Connecticut Utility McGuireWoods advised John Laing Group, a leading international investor and active manager of core infrastructure assets, on its financing for the acquisition of a Connecticut water system serving 735,000 people in 60 municipalities. John Laing supported Aquarion Water Authority (AWA), which was formed by Connecticut lawmakers in 2024, in its purchase of the Aquarion Company from Eversource. John Laing's roleis part of a broader financing solution, which includes a public bond issuance led by Bank of America and included Barclays as an additional underwriter.
McGuireWoods partners Jake Spilman and Douglas Lamb led the deal team. Other key members of the deal team included counsel Clinton Randolph and Ryan Thompson, partner Robert Kaplan and associate Johnny Mac Yates.
"We were proud to assist John Laing with this transaction and for our continued partnership with John Laing," Spilman said. "The deal reflects John Laing's commitment to providing innovative financing to support essential infrastructure."
McGuireWoods' full-service team of lawyers work cohesively with colleagues in all of the firm's groups to deliver end-to-end deal support tailored to each transaction.
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URL: John Laing Group
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Original text here: https://www.mcguirewoods.com/news/press-releases/2026/7/mcguirewoods-represents-john-laing-group-in-financing-acquisition-of-connecticut-utility/
[Category: BizLaw/Legal]
Market Participant Firms Making Significant Progress Toward U.S. Treasury Cash Clearing Deadline, According to Latest DTCC Survey
NEW YORK, July 28 (TNSxrep) [Category: BizFinancial Services] -- The Depository Trust and Clearing Corp., a provider of clearing and settlement services to the financial markets, issued the following news release on July 27, 2026:
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Market Participant Firms Making Significant Progress Toward U.S. Treasury Cash Clearing Deadline, According to Latest DTCC Survey
New FICC survey shows market converging on central clearing at scale, with most firms already operationally ready
Over $1.2 trillion in daily Treasury cash activity already centrally cleared by FICC ahead of the SEC mandate
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New ... Show Full Article NEW YORK, July 28 (TNSxrep) [Category: BizFinancial Services] -- The Depository Trust and Clearing Corp., a provider of clearing and settlement services to the financial markets, issued the following news release on July 27, 2026: * * * Market Participant Firms Making Significant Progress Toward U.S. Treasury Cash Clearing Deadline, According to Latest DTCC Survey New FICC survey shows market converging on central clearing at scale, with most firms already operationally ready Over $1.2 trillion in daily Treasury cash activity already centrally cleared by FICC ahead of the SEC mandate - NewYork/London/Hong Kong/Singapore/Sydney - The Depository Trust & Clearing Corporation (DTCC), the premier post-trade market infrastructure for the global financial services industry, today announced the publication of its latest report, Industry Readiness for U.S. Treasury Cash Clearing: A Survey of FICC Membership, offering one of the most comprehensive views of the industry's preparedness ahead of the upcoming U.S. Treasury cash clearing mandate.
The survey, sent to all full-service Netting Members of DTCC's Fixed Income Clearing Corporation (FICC) Government Securities Division (GSD), found that market participants have made substantial progress toward implementation, with most respondents reporting they are already prepared or actively completing final readiness activities ahead of the December 31, 2026, Treasury cash clearing compliance date.
Results indicate that while implementation efforts remain ongoing, the industry has already migrated a significant portion of Treasury cash activity into central clearing and established much of the infrastructure needed to meet the mandate. Among the report's key findings:
* Over $1.2 Trillion Treasury Cash Activity Already Clearing at FICC; Estimated $300-400 Billion Left to Go. GSD Netting Member respondents reported approximately $300-400 billion in average daily par value of Treasury cash activity that is not currently submitted for clearing. While not an insignificant amount, the industry has already migrated more than three times that amount into central clearing at FICC ahead of the mandate deadline.
* Most of the Industry Is Already Prepared for the Treasury Cash Clearing Deadline. 79% of GSD Netting Member respondents reported already having the necessary account setups in place at FICC ahead of the year-end Treasury cash clearing deadline, and nearly 100% of respondents requiring an FICC account have either established one or have actively entered FICC's onboarding pipeline.
* Approximately One-Third of Dealers Expect to Offer Treasury Cash Clearing to Their Clients. Approximately one-third of GSD Netting Member respondents reported that they expect to provide clearing services for their clients' Treasury cash activity, which is generally consistent with the percentage of dealers who offer client clearing services for Treasury repo and/or Treasury cash activity today at FICC.
The report also highlights the scale of the infrastructure supporting the transition. Across all of its cash and repo clearing activity, FICC currently clears more than $12 trillion in average daily transactions, with activity levels increasing 165% since the Securities and Exchange Commission (SEC) first proposed the Treasury clearing mandate. FICC's Sponsored Service now supports more than 2,850 Sponsored Members across 66 eligible Sponsored Member jurisdictions, processing over $2.5 trillion in average daily volume. Volume in the Sponsored Service has also grown 771% since the SEC proposed the Treasury Clearing mandate in September 2022.
"These findings reinforce what we're seeing across the marketplace: firms have been actively preparing for expanded U.S. Treasury clearing requirements and are making meaningful progress toward implementation," said Laura Klimpel, Managing Director and Head of DTCC's Fixed Income and Financing Solutions business.
"Since the SEC first proposed the Treasury clearing mandate, FICC has worked extensively with market participants to expand access to central clearing, enhance our onboarding capabilities, increase processing capacity, and introduce new solutions designed to support a broader range of market participants and clearing models," said Brian Steele, President of Clearing & Securities Services at DTCC. "We believe the industry is well positioned for the Treasury cash clearing deadline on December 31, 2026, and we remain focused on supporting firms as preparations continue for both the cash clearing requirement and the repo clearing deadline on June 30, 2027."
Over the past several years, FICC has introduced a number of enhancements designed to support increased clearing activity and improve market access. These include continued expansion of the Sponsored Service, the launch of new cross-margining capabilities through the FICC-CME Cross-Margining Program, enhanced tri-party repo clearing solutions such as the Sponsored GC Collateral-in-Lieu (CIL) and Agent Clearing Tri-Party services, and additional intermediation models that provide firms with greater flexibility in how they access central clearing.
The report also outlines future initiatives intended to further strengthen the Treasury clearing ecosystem, including FICC's proposed Guaranty Fund Enhancement and planned GSD / Mortgage Backed Securities Division (MBSD) Portfolio Margining Service, both subject to regulatory approval.
"While much of the industry's focus is rightly on mandate readiness, innovation across the clearing ecosystem continues," Klimpel added. "As the market continues to evolve, our focus remains on delivering scalable, resilient infrastructure and flexible clearing solutions that support a successful transition to expanded central clearing and continue to strengthen the U.S. Treasury market over the long term."
* * *
Notes to Editor
The survey was distributed to all existing full-service Netting Members of FICC's Government Securities Division (GSD) and achieved a 92% response rate, providing a broad view of industry preparedness.
* * *
About DTCC
With over 50 years of experience, DTCC is the premier post-trade market infrastructure for the global financial services industry. From 20 locations around the world, DTCC, through its subsidiaries, automates, centralizes, and standardizes the processing of financial transactions, mitigating risk, increasing transparency, enhancing performance and driving efficiency for thousands of broker/dealers, custodian banks and asset managers. Industry owned and governed, the firm innovates purposefully, simplifying the complexities of clearing, settlement, asset servicing, transaction processing, trade reporting and data services across asset classes, bringing enhanced resilience and soundness to existing financial markets while advancing the digital asset ecosystem. In 2025, DTCC's subsidiaries processed securities transactions valued at U.S. $4.7 quadrillion and its depository subsidiary provided custody and asset servicing for securities issues from over 150 countries and territories valued at U.S. $114 trillion. DTCC's Global Trade Repository service, through locally registered, licensed, or approved trade repositories, processes more than 25 billion messages annually. To learn more, please visit us at www.dtcc.com or connect with us on LinkedIn, X, YouTube, Facebook and Instagram.
* * *
Original text here: https://www.dtcc.com/news/2026/july/27/dtcc-survey-firms-progress-toward-us-treasury-clearing-deadline
* * *
Market Participant Firms Making Significant Progress Toward U.S. Treasury Cash Clearing Deadline, According to Latest DTCC Survey
New FICC survey shows market converging on central clearing at scale, with most firms already operationally ready
Over $1.2 trillion in daily Treasury cash activity already centrally cleared by FICC ahead of the SEC mandate
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New ... Show Full Article NEW YORK, July 28 (TNSxrep) [Category: BizFinancial Services] -- The Depository Trust and Clearing Corp., a provider of clearing and settlement services to the financial markets, issued the following news release on July 27, 2026: * * * Market Participant Firms Making Significant Progress Toward U.S. Treasury Cash Clearing Deadline, According to Latest DTCC Survey New FICC survey shows market converging on central clearing at scale, with most firms already operationally ready Over $1.2 trillion in daily Treasury cash activity already centrally cleared by FICC ahead of the SEC mandate - NewYork/London/Hong Kong/Singapore/Sydney - The Depository Trust & Clearing Corporation (DTCC), the premier post-trade market infrastructure for the global financial services industry, today announced the publication of its latest report, Industry Readiness for U.S. Treasury Cash Clearing: A Survey of FICC Membership, offering one of the most comprehensive views of the industry's preparedness ahead of the upcoming U.S. Treasury cash clearing mandate.
The survey, sent to all full-service Netting Members of DTCC's Fixed Income Clearing Corporation (FICC) Government Securities Division (GSD), found that market participants have made substantial progress toward implementation, with most respondents reporting they are already prepared or actively completing final readiness activities ahead of the December 31, 2026, Treasury cash clearing compliance date.
Results indicate that while implementation efforts remain ongoing, the industry has already migrated a significant portion of Treasury cash activity into central clearing and established much of the infrastructure needed to meet the mandate. Among the report's key findings:
* Over $1.2 Trillion Treasury Cash Activity Already Clearing at FICC; Estimated $300-400 Billion Left to Go. GSD Netting Member respondents reported approximately $300-400 billion in average daily par value of Treasury cash activity that is not currently submitted for clearing. While not an insignificant amount, the industry has already migrated more than three times that amount into central clearing at FICC ahead of the mandate deadline.
* Most of the Industry Is Already Prepared for the Treasury Cash Clearing Deadline. 79% of GSD Netting Member respondents reported already having the necessary account setups in place at FICC ahead of the year-end Treasury cash clearing deadline, and nearly 100% of respondents requiring an FICC account have either established one or have actively entered FICC's onboarding pipeline.
* Approximately One-Third of Dealers Expect to Offer Treasury Cash Clearing to Their Clients. Approximately one-third of GSD Netting Member respondents reported that they expect to provide clearing services for their clients' Treasury cash activity, which is generally consistent with the percentage of dealers who offer client clearing services for Treasury repo and/or Treasury cash activity today at FICC.
The report also highlights the scale of the infrastructure supporting the transition. Across all of its cash and repo clearing activity, FICC currently clears more than $12 trillion in average daily transactions, with activity levels increasing 165% since the Securities and Exchange Commission (SEC) first proposed the Treasury clearing mandate. FICC's Sponsored Service now supports more than 2,850 Sponsored Members across 66 eligible Sponsored Member jurisdictions, processing over $2.5 trillion in average daily volume. Volume in the Sponsored Service has also grown 771% since the SEC proposed the Treasury Clearing mandate in September 2022.
"These findings reinforce what we're seeing across the marketplace: firms have been actively preparing for expanded U.S. Treasury clearing requirements and are making meaningful progress toward implementation," said Laura Klimpel, Managing Director and Head of DTCC's Fixed Income and Financing Solutions business.
"Since the SEC first proposed the Treasury clearing mandate, FICC has worked extensively with market participants to expand access to central clearing, enhance our onboarding capabilities, increase processing capacity, and introduce new solutions designed to support a broader range of market participants and clearing models," said Brian Steele, President of Clearing & Securities Services at DTCC. "We believe the industry is well positioned for the Treasury cash clearing deadline on December 31, 2026, and we remain focused on supporting firms as preparations continue for both the cash clearing requirement and the repo clearing deadline on June 30, 2027."
Over the past several years, FICC has introduced a number of enhancements designed to support increased clearing activity and improve market access. These include continued expansion of the Sponsored Service, the launch of new cross-margining capabilities through the FICC-CME Cross-Margining Program, enhanced tri-party repo clearing solutions such as the Sponsored GC Collateral-in-Lieu (CIL) and Agent Clearing Tri-Party services, and additional intermediation models that provide firms with greater flexibility in how they access central clearing.
The report also outlines future initiatives intended to further strengthen the Treasury clearing ecosystem, including FICC's proposed Guaranty Fund Enhancement and planned GSD / Mortgage Backed Securities Division (MBSD) Portfolio Margining Service, both subject to regulatory approval.
"While much of the industry's focus is rightly on mandate readiness, innovation across the clearing ecosystem continues," Klimpel added. "As the market continues to evolve, our focus remains on delivering scalable, resilient infrastructure and flexible clearing solutions that support a successful transition to expanded central clearing and continue to strengthen the U.S. Treasury market over the long term."
* * *
Notes to Editor
The survey was distributed to all existing full-service Netting Members of FICC's Government Securities Division (GSD) and achieved a 92% response rate, providing a broad view of industry preparedness.
* * *
About DTCC
With over 50 years of experience, DTCC is the premier post-trade market infrastructure for the global financial services industry. From 20 locations around the world, DTCC, through its subsidiaries, automates, centralizes, and standardizes the processing of financial transactions, mitigating risk, increasing transparency, enhancing performance and driving efficiency for thousands of broker/dealers, custodian banks and asset managers. Industry owned and governed, the firm innovates purposefully, simplifying the complexities of clearing, settlement, asset servicing, transaction processing, trade reporting and data services across asset classes, bringing enhanced resilience and soundness to existing financial markets while advancing the digital asset ecosystem. In 2025, DTCC's subsidiaries processed securities transactions valued at U.S. $4.7 quadrillion and its depository subsidiary provided custody and asset servicing for securities issues from over 150 countries and territories valued at U.S. $114 trillion. DTCC's Global Trade Repository service, through locally registered, licensed, or approved trade repositories, processes more than 25 billion messages annually. To learn more, please visit us at www.dtcc.com or connect with us on LinkedIn, X, YouTube, Facebook and Instagram.
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Original text here: https://www.dtcc.com/news/2026/july/27/dtcc-survey-firms-progress-toward-us-treasury-clearing-deadline
Hackett Group Finds SG&A Costs Reach Five-Year Highs Across North America and Europe
MIAMI, July 28 (TNSrep) -- The Hackett Group, a consulting and executive advisory firm, issued the following news release on July 27, 2026:
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The Hackett Group(R) Finds SG&A Costs Reach Five-Year Highs Across North America and Europe
New research shows the next generation of profitable growth will be driven by AI-enabled operating models
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The Hackett Group, Inc. (NASDAQ: HCKT), an ROI-led AI transformation firm, today announced findings from both its North America and European 2026 SG&A Cost Study and Scorecard, revealing that the next generation of profitable growth will be driven less ... Show Full Article MIAMI, July 28 (TNSrep) -- The Hackett Group, a consulting and executive advisory firm, issued the following news release on July 27, 2026: * * * The Hackett Group(R) Finds SG&A Costs Reach Five-Year Highs Across North America and Europe New research shows the next generation of profitable growth will be driven by AI-enabled operating models - The Hackett Group, Inc. (NASDAQ: HCKT), an ROI-led AI transformation firm, today announced findings from both its North America and European 2026 SG&A Cost Study and Scorecard, revealing that the next generation of profitable growth will be driven lessby economic conditions and more by AI-enabled operating models. The average costs of selling, general and administrative (SG&A) functions climbed to their highest levels in five years across both regions, exposing a widening gap between organizations that are improving productivity through artificial intelligence (AI) and those relying on traditional cost-management approaches. This was against a background of stronger revenue growth and moderating inflation.
Among the 1,000 largest publicly traded companies analyzed in each region, median SG&A costs rose to 16.2% of revenue in North America and 13.4% in Europe. Revenue growth accelerated to 4.4% in North America and 6.5% in Europe during 2025, yet many organizations continued to struggle to translate growth into sustainable operating leverage.
While fewer organizations experienced worsening SG&A performance than the previous year, much of the improvement reflected stronger revenue growth rather than fundamental gains in productivity. In North America, the share of companies whose SG&A costs grew faster than revenue declined from 62.0% to 51.6%, while in Europe it fell from 62.5% to 53.6%. The findings show that relatively few organizations have fundamentally improved the productivity and scalability of their operating models.
"Economic recovery improved financial results, but it didn't fundamentally change how organizations operate," said Thomas Kellaway, principal at The Hackett Group(R). "The next generation of profitable growth will come from AI-enabled operating models that increase productivity, scale more efficiently and strengthen operating leverage."
A widening operational leverage gap
The gap between leading organizations and median companies continued to widen across both regions. In North America, first-quartile companies operated with SG&A costs equal to 7.8% of revenue, compared to 16.2% for the median - an 8.4-percentage-point advantage between first-quartile and median companies. In Europe, first-quartile companies reported SG&A costs of 6.1% of revenue versus 13.4% for the median - a 7.3-percentage-point advantage.
The research also highlights a growing scalability challenge. Many companies generated only a narrow margin between revenue growth and SG&A cost growth, leaving them increasingly vulnerable if market conditions weaken. The widening gap between leading and median performance suggests that relatively few organizations have built the productivity and scalability needed to create sustainable operating leverage through AI-enabled operating models.
AI is reshaping SG&A economics
When embedded into core business processes, AI is helping organizations improve productivity, scale more efficiently, and create structural SG&A cost advantages. For a typical $10 billion company, achieving Digital World Class(R) performance across SG&A functions represents approximately $286 million in annual cost advantage. Across finance, human resources, information technology and procurement alone, the potential annual cost advantage approaches $85 million.
Leading organizations are investing accordingly. Digital World Class(R) technology organizations allocate three times more of their technology spending to AI, intelligent automation and other emerging technologies than their peers, creating the productivity and scalability advantages that drive long-term operating leverage.
The Hackett Group(R) expects the performance gap between AI World Class organizations and typical companies to widen by up to 75% in the near term as leaders embed AI into core business processes.
How AI is transforming SG&A performance
The research highlights several examples of how AI, Gen AI and agentic AI are already transforming critical SG&A processes, including:
* Contract intelligence: 30%-50% faster milestone payment processing and 30%-40% faster change-order cycles
* Autonomous financial close: close cycles accelerated by 2-3 days with 40%-60% better commentary quality and consistency
* AI-powered compliance: 70%-80% faster policy lookup, 50%-60% fewer policy interpretation errors and always-on compliance guidance
Collectively, these examples demonstrate AI's potential to reduce costs, improve productivity and free employees to focus on higher-value work.
Priorities for building AI-enabled SG&A performance
Based on the findings, The Hackett Group(R) identified six priorities for organizations seeking to improve SG&A performance, including:
1. Map end-to-end processes
2. Simplify and standardize work
3. Embed AI into core operations
4. Measure return on AI investments
5. Develop AI-ready talent
6. Strengthen strategic sourcing
"The next competitive advantage will not be determined by rates of AI adoption," said Murray Shevlin, principal at The Hackett Group(R). "It will come from redesigning end-to-end processes, so AI delivers measurable gains in productivity, operating leverage and profitable growth.
* * *
About the research
The North America SG&A Cost Study and Scorecard analyzed the financial performance of the 1,000 largest publicly traded nonfinancial services companies headquartered in North America. The European SG&A Cost Study and Scorecard analyzed the financial performance of the 1,000 largest publicly traded nonfinancial services companies headquartered in Europe. Both studies examined fiscal year 2025 financial results.
Download the North America SG&A Cost Study and Scorecard (https://go.poweredbyhackett.com/26nasga2607nr) and the European SG&A Cost Study and Scorecard (https://go.poweredbyhackett.com/26eusga2607nr) for full insights.
* * *
About The Hackett Group(R)
The Hackett Group, Inc. (NASDAQ: HCKT) is an ROI-led, AI enterprise transformation firm that helps clients enable AI world-class performance. Its experts and engineers leverage proprietary AI delivery platforms - Hackett AI XPLR(TM), ZBrain(TM), XT(TM), AIXelerator(TM) and AskHackett(TM) - to accelerate and enhance the delivery of the company's solutions and services.
The AI platforms are powered by the company's domain-specific Hackett Solution Language Model informed by Hackett Process and Performance Intelligence - including Digital World Class(R) benchmark metrics, best-practice process flows and service delivery model solution frameworks, which accelerate and enhance the delivery of its services. The Hackett Group's proprietary insights are based on benchmarking results from leading global organizations, including 98% of Dow Jones Global Titans, 97% of the Dow Jones Industrials and 90% of the Fortune 100. Visit www.thehackettgroup.com.
* * *
Cautionary Statement Regarding "Forward-Looking" Statements
This release contains "forward-looking" statements within the meaning of Section 27A of the Securities Act of 1933 as amended and Section 21E of the Securities Exchange Act of 1934, as amended. Statements including without limitation, words such as "expects," "anticipates," "intends," "plans," "believes," "seeks," "estimates," or other similar phrases or variations of such words or similar expressions indicating, present or future anticipated or expected occurrences or outcomes are intended to identify such forward-looking statements. Forward-looking statements are not statements of historical fact and involve known and unknown risks, uncertainties and other factors that may cause the Company's actual results, performance or achievements to be materially different from the results, performance or achievements expressed or implied by the forward-looking statements. Factors that may impact such forward-looking statements include without limitation, the ability of The Hackett Group(R) to effectively market its digital transformation services, our ability to transition our capabilities to support generative artificial intelligence (AI)-related consulting services and solutions and other consulting services, our ability to effectively integrate acquisitions into our operations, our ability to manage joint ventures and successfully cooperate with our joint venture partners, competition from other consulting and technology companies that may have or develop in the future, similar offerings, the commercial viability of The Hackett Group(R) and its services as well as other risk detailed in The Hackett Group's reports filed with the United States Securities and Exchange Commission. The Hackett Group(R) does not undertake any duty to update this release or any forward-looking statements contained herein.
* * *
Original text here: https://www.thehackettgroup.com/the-hackett-group-finds-sga-costs-reach-five-year-highs-across-north-america-and-europe/
[Category: BizConsulting]
* * *
The Hackett Group(R) Finds SG&A Costs Reach Five-Year Highs Across North America and Europe
New research shows the next generation of profitable growth will be driven by AI-enabled operating models
-
The Hackett Group, Inc. (NASDAQ: HCKT), an ROI-led AI transformation firm, today announced findings from both its North America and European 2026 SG&A Cost Study and Scorecard, revealing that the next generation of profitable growth will be driven less ... Show Full Article MIAMI, July 28 (TNSrep) -- The Hackett Group, a consulting and executive advisory firm, issued the following news release on July 27, 2026: * * * The Hackett Group(R) Finds SG&A Costs Reach Five-Year Highs Across North America and Europe New research shows the next generation of profitable growth will be driven by AI-enabled operating models - The Hackett Group, Inc. (NASDAQ: HCKT), an ROI-led AI transformation firm, today announced findings from both its North America and European 2026 SG&A Cost Study and Scorecard, revealing that the next generation of profitable growth will be driven lessby economic conditions and more by AI-enabled operating models. The average costs of selling, general and administrative (SG&A) functions climbed to their highest levels in five years across both regions, exposing a widening gap between organizations that are improving productivity through artificial intelligence (AI) and those relying on traditional cost-management approaches. This was against a background of stronger revenue growth and moderating inflation.
Among the 1,000 largest publicly traded companies analyzed in each region, median SG&A costs rose to 16.2% of revenue in North America and 13.4% in Europe. Revenue growth accelerated to 4.4% in North America and 6.5% in Europe during 2025, yet many organizations continued to struggle to translate growth into sustainable operating leverage.
While fewer organizations experienced worsening SG&A performance than the previous year, much of the improvement reflected stronger revenue growth rather than fundamental gains in productivity. In North America, the share of companies whose SG&A costs grew faster than revenue declined from 62.0% to 51.6%, while in Europe it fell from 62.5% to 53.6%. The findings show that relatively few organizations have fundamentally improved the productivity and scalability of their operating models.
"Economic recovery improved financial results, but it didn't fundamentally change how organizations operate," said Thomas Kellaway, principal at The Hackett Group(R). "The next generation of profitable growth will come from AI-enabled operating models that increase productivity, scale more efficiently and strengthen operating leverage."
A widening operational leverage gap
The gap between leading organizations and median companies continued to widen across both regions. In North America, first-quartile companies operated with SG&A costs equal to 7.8% of revenue, compared to 16.2% for the median - an 8.4-percentage-point advantage between first-quartile and median companies. In Europe, first-quartile companies reported SG&A costs of 6.1% of revenue versus 13.4% for the median - a 7.3-percentage-point advantage.
The research also highlights a growing scalability challenge. Many companies generated only a narrow margin between revenue growth and SG&A cost growth, leaving them increasingly vulnerable if market conditions weaken. The widening gap between leading and median performance suggests that relatively few organizations have built the productivity and scalability needed to create sustainable operating leverage through AI-enabled operating models.
AI is reshaping SG&A economics
When embedded into core business processes, AI is helping organizations improve productivity, scale more efficiently, and create structural SG&A cost advantages. For a typical $10 billion company, achieving Digital World Class(R) performance across SG&A functions represents approximately $286 million in annual cost advantage. Across finance, human resources, information technology and procurement alone, the potential annual cost advantage approaches $85 million.
Leading organizations are investing accordingly. Digital World Class(R) technology organizations allocate three times more of their technology spending to AI, intelligent automation and other emerging technologies than their peers, creating the productivity and scalability advantages that drive long-term operating leverage.
The Hackett Group(R) expects the performance gap between AI World Class organizations and typical companies to widen by up to 75% in the near term as leaders embed AI into core business processes.
How AI is transforming SG&A performance
The research highlights several examples of how AI, Gen AI and agentic AI are already transforming critical SG&A processes, including:
* Contract intelligence: 30%-50% faster milestone payment processing and 30%-40% faster change-order cycles
* Autonomous financial close: close cycles accelerated by 2-3 days with 40%-60% better commentary quality and consistency
* AI-powered compliance: 70%-80% faster policy lookup, 50%-60% fewer policy interpretation errors and always-on compliance guidance
Collectively, these examples demonstrate AI's potential to reduce costs, improve productivity and free employees to focus on higher-value work.
Priorities for building AI-enabled SG&A performance
Based on the findings, The Hackett Group(R) identified six priorities for organizations seeking to improve SG&A performance, including:
1. Map end-to-end processes
2. Simplify and standardize work
3. Embed AI into core operations
4. Measure return on AI investments
5. Develop AI-ready talent
6. Strengthen strategic sourcing
"The next competitive advantage will not be determined by rates of AI adoption," said Murray Shevlin, principal at The Hackett Group(R). "It will come from redesigning end-to-end processes, so AI delivers measurable gains in productivity, operating leverage and profitable growth.
* * *
About the research
The North America SG&A Cost Study and Scorecard analyzed the financial performance of the 1,000 largest publicly traded nonfinancial services companies headquartered in North America. The European SG&A Cost Study and Scorecard analyzed the financial performance of the 1,000 largest publicly traded nonfinancial services companies headquartered in Europe. Both studies examined fiscal year 2025 financial results.
Download the North America SG&A Cost Study and Scorecard (https://go.poweredbyhackett.com/26nasga2607nr) and the European SG&A Cost Study and Scorecard (https://go.poweredbyhackett.com/26eusga2607nr) for full insights.
* * *
About The Hackett Group(R)
The Hackett Group, Inc. (NASDAQ: HCKT) is an ROI-led, AI enterprise transformation firm that helps clients enable AI world-class performance. Its experts and engineers leverage proprietary AI delivery platforms - Hackett AI XPLR(TM), ZBrain(TM), XT(TM), AIXelerator(TM) and AskHackett(TM) - to accelerate and enhance the delivery of the company's solutions and services.
The AI platforms are powered by the company's domain-specific Hackett Solution Language Model informed by Hackett Process and Performance Intelligence - including Digital World Class(R) benchmark metrics, best-practice process flows and service delivery model solution frameworks, which accelerate and enhance the delivery of its services. The Hackett Group's proprietary insights are based on benchmarking results from leading global organizations, including 98% of Dow Jones Global Titans, 97% of the Dow Jones Industrials and 90% of the Fortune 100. Visit www.thehackettgroup.com.
* * *
Cautionary Statement Regarding "Forward-Looking" Statements
This release contains "forward-looking" statements within the meaning of Section 27A of the Securities Act of 1933 as amended and Section 21E of the Securities Exchange Act of 1934, as amended. Statements including without limitation, words such as "expects," "anticipates," "intends," "plans," "believes," "seeks," "estimates," or other similar phrases or variations of such words or similar expressions indicating, present or future anticipated or expected occurrences or outcomes are intended to identify such forward-looking statements. Forward-looking statements are not statements of historical fact and involve known and unknown risks, uncertainties and other factors that may cause the Company's actual results, performance or achievements to be materially different from the results, performance or achievements expressed or implied by the forward-looking statements. Factors that may impact such forward-looking statements include without limitation, the ability of The Hackett Group(R) to effectively market its digital transformation services, our ability to transition our capabilities to support generative artificial intelligence (AI)-related consulting services and solutions and other consulting services, our ability to effectively integrate acquisitions into our operations, our ability to manage joint ventures and successfully cooperate with our joint venture partners, competition from other consulting and technology companies that may have or develop in the future, similar offerings, the commercial viability of The Hackett Group(R) and its services as well as other risk detailed in The Hackett Group's reports filed with the United States Securities and Exchange Commission. The Hackett Group(R) does not undertake any duty to update this release or any forward-looking statements contained herein.
* * *
Original text here: https://www.thehackettgroup.com/the-hackett-group-finds-sga-costs-reach-five-year-highs-across-north-america-and-europe/
[Category: BizConsulting]
Faegre Drinker Issues Commentary: DOJ Returns to Targeted Second Request Investigations, Publishes Model Timing Agreement
MINNEAPOLIS, Minnesota, July 28 -- Faegre Drinker Biddle and Reath, a law firm, issued the following commentary on July 27, 2026, by counsel Anna M. Behrmann, associate Mihajlo Gasic and partners Matthew R. Levy and Kathy L. Osborn:
* * *
DOJ Returns to Targeted Second Request Investigations, Publishes Model Timing Agreement
Streamlined Process Signals Continued Pro-Business Approach to Merger Review under the Second Trump Administration
At a Glance
* On July 23, 2026, the DOJ announced it is resuming targeted second request investigations and published a model timing agreement to expedite ... Show Full Article MINNEAPOLIS, Minnesota, July 28 -- Faegre Drinker Biddle and Reath, a law firm, issued the following commentary on July 27, 2026, by counsel Anna M. Behrmann, associate Mihajlo Gasic and partners Matthew R. Levy and Kathy L. Osborn: * * * DOJ Returns to Targeted Second Request Investigations, Publishes Model Timing Agreement Streamlined Process Signals Continued Pro-Business Approach to Merger Review under the Second Trump Administration At a Glance * On July 23, 2026, the DOJ announced it is resuming targeted second request investigations and published a model timing agreement to expeditemerger review under the HSR Act, replacing the broader investigative approach adopted during the Biden administration.
* The announcement reflects the Trump administration's broader effort to reduce regulatory burdens on deal parties while maintaining antitrust enforcement, including a return to consent decrees and structural remedies over litigation to block deals.
* Companies should expect shorter, less costly second request processes from the DOJ, but proactive engagement with regulators and awareness of expanding state-level enforcement remain critical.
-
On July 23, 2026, the Department of Justice's Antitrust Division (DOJ) announced it has returned to implementing targeted Second Request investigations to expedite merger review under the Hart-Scott-Rodino (HSR) Act. The DOJ also published a model timing agreement in connection with the announcement. Together, these actions represent the latest in a series of steps by the Trump administration to reduce regulatory burdens on merging parties while preserving the government's ability to investigate transactions that raise potential competitive concerns.
Background
Under the HSR Act, mergers and other transactions above certain financial thresholds must be reported to the DOJ and the Federal Trade Commission (FTC) before closing. If either agency identifies potential competition concerns, it may issue a "second request" -- a formal demand for additional documents and information -- that typically adds months to deal timelines and imposes significant compliance costs. Prior to the Biden administration, the DOJ and the FTC routinely executed targeted second request investigations, entering into timing agreements with merging parties that prioritized the submission of information most relevant to the agencies' competitive concerns. After reviewing this priority information, the reviewing agency could close its investigation, modify or narrow the second request, or require full compliance.
The Biden administration moved away from this targeted approach in favor of broader investigations. The Biden-era FTC also adopted sweeping changes to the HSR notification form that roughly tripled average preparation time, but those amended rules were subsequently vacated by the Eastern District of Texas. Merging parties currently file under the pre-2025 form while the agencies solicit public comment on a revised HSR form.
The Announcement
Associate Attorney General Stanley E. Woodward Jr. framed the return to targeted reviews as an effort "to eliminate bureaucratic burdens while still preserving the integrity of second request investigations." He further stated the change "will allow for quicker and more efficient review of proposed transactions; more effective use of taxpayer resources; and above all, helps the [DOJ] do its job to safeguard a competitive marketplace while keeping America open for business."
The model timing agreement outlines the mechanics of the targeted process. Under the agreement, the parties commit to an expedited production of "priority" documents and information the DOJ has identified as most pertinent to resolving its competitive questions. Following review of the priority production, the DOJ will notify the parties whether it intends to: (1) close the investigation or grant early termination; (2) modify or narrow the second request; or (3) proceed with the investigation and require full compliance with the original second request.
Importantly, the DOJ emphasized that it "remains open to good faith negotiations regarding modifications to second requests in all cases" and "will continue to require full compliance in circumstances in which broader information is necessary to reach an enforcement decision."
While this announcement applies only to the DOJ, the FTC Chair Andrew Ferguson has signaled a broadly aligned philosophy, stating the FTC "must get out of the way quickly" when a merger does not violate antitrust laws "to avoid bogging down innovation and interfering with the forces of a free and competitive market."
M&A Enforcement under the Trump Administration
This announcement is part of the Trump administration's broader approach to merger enforcement. The current administration has consistently signaled its preference for reducing procedural hurdles on deal parties while not materially decreasing antitrust enforcement activity.
Enforcement by the Numbers
The recently released FY2025 HSR Annual Report, covering October 2024 through September 2025, provides a useful snapshot of the transition between administrations. The agencies issued 41 second requests in FY2025, representing 2.1% of notified transactions -- a slight decrease from FY2024's 3.0% rate but consistent with the long-standing average of approximately 2-3%. Total merger enforcement actions dropped from 32 in FY2024 to 18 in FY2025.
Return of Consent Decrees
The early dip in enforcement actions may reflect the second Trump administration's preference for settlement. During the Biden administration, agencies strongly favored litigation to block deals rather than negotiated settlements. The second Trump administration has returned to accepting structural remedies (e.g., divestitures) and behavioral commitments as the primary tools for resolving competition concerns.
Broader Themes
The second Trump administration also has articulated an "America first" antitrust framework, with enforcement priorities oriented toward protecting workers, consumers, small businesses, and US manufacturing. Industries in the crosshairs of the administration's policy priorities -- such as agriculture, health care, labor, technology, and manufacturing -- continue to draw focused scrutiny, while the agencies have signaled greater willingness to clear transactions quickly in other sectors.
Implications for Transacting Parties
For companies contemplating M&A transactions during the remainder of the second Trump administration, we note the following practical considerations.
Reduced Second Request Timelines and Costs
Parties that receive a second request from the DOJ should anticipate greater willingness to negotiate the scope of production, prioritize targeted submissions, and engage in constructive dialogue about the DOJ's competitive concerns. This should translate into shorter investigations and lower compliance costs for many transactions.
Proactive Engagement Remains Critical
The availability of a targeted process places a premium on early and substantive engagement with the DOJ. Parties and their counsel should be prepared to identify and address the DOJ's likely competition concerns proactively, offering to prioritize relevant information to facilitate a more efficient review. For high-profile or politically sensitive transactions, companies also should consider developing a broader engagement strategy that accounts for the White House's increasingly direct role in antitrust enforcement decisions during this administration.
State Enforcement May Intensify
Companies also should be mindful that state attorneys general may seek to fill any perceived gaps in federal enforcement. Multiple states have enacted or expanded their own premerger notification regimes, and multistate coalitions have shown a willingness to investigate and prosecute transactions independently of -- and at times in opposition to -- the enforcement decisions of federal authorities.
In Conclusion
The antitrust laws are nuanced and complex and their application to specific transactions is fact sensitive. We strongly recommend that companies contemplating a merger or acquisition consult with experienced antitrust and HSR counsel early in the deal process to navigate the current regulatory landscape and develop an effective engagement strategy.
* * *
The material contained in this communication is informational, general in nature and does not constitute legal advice. The material contained in this communication should not be relied upon or used without consulting a lawyer to consider your specific circumstances. This communication was published on the date specified and may not include any changes in the topics, laws, rules or regulations covered. Receipt of this communication does not establish an attorney-client relationship. In some jurisdictions, this communication may be considered attorney advertising.
* * *
Meet the Authors
Anna M. Behrmann
Counsel
Indianapolis
+1 317 237 1016
anna.behrmann@faegredrinker.com
* * *
Kathy L. Osborn
Partner
Indianapolis
+1 317 237 8261
kathy.osborn@faegredrinker.com
* * *
Matthew R. Levy
Partner
Indianapolis
+1 317 237 1114
matthew.levy@faegredrinker.com
* * *
Mihajlo Gasic
Associate
Chicago
+1 312 569 1142
mihajlo.gasic@faegredrinker.com
* * *
Original text here: https://www.faegredrinker.com/en/insights/publications/2026/7/doj-returns-to-targeted-second-request-investigations-publishes-model-timing-agreement
[Category: BizLaw/Legal]
* * *
DOJ Returns to Targeted Second Request Investigations, Publishes Model Timing Agreement
Streamlined Process Signals Continued Pro-Business Approach to Merger Review under the Second Trump Administration
At a Glance
* On July 23, 2026, the DOJ announced it is resuming targeted second request investigations and published a model timing agreement to expedite ... Show Full Article MINNEAPOLIS, Minnesota, July 28 -- Faegre Drinker Biddle and Reath, a law firm, issued the following commentary on July 27, 2026, by counsel Anna M. Behrmann, associate Mihajlo Gasic and partners Matthew R. Levy and Kathy L. Osborn: * * * DOJ Returns to Targeted Second Request Investigations, Publishes Model Timing Agreement Streamlined Process Signals Continued Pro-Business Approach to Merger Review under the Second Trump Administration At a Glance * On July 23, 2026, the DOJ announced it is resuming targeted second request investigations and published a model timing agreement to expeditemerger review under the HSR Act, replacing the broader investigative approach adopted during the Biden administration.
* The announcement reflects the Trump administration's broader effort to reduce regulatory burdens on deal parties while maintaining antitrust enforcement, including a return to consent decrees and structural remedies over litigation to block deals.
* Companies should expect shorter, less costly second request processes from the DOJ, but proactive engagement with regulators and awareness of expanding state-level enforcement remain critical.
-
On July 23, 2026, the Department of Justice's Antitrust Division (DOJ) announced it has returned to implementing targeted Second Request investigations to expedite merger review under the Hart-Scott-Rodino (HSR) Act. The DOJ also published a model timing agreement in connection with the announcement. Together, these actions represent the latest in a series of steps by the Trump administration to reduce regulatory burdens on merging parties while preserving the government's ability to investigate transactions that raise potential competitive concerns.
Background
Under the HSR Act, mergers and other transactions above certain financial thresholds must be reported to the DOJ and the Federal Trade Commission (FTC) before closing. If either agency identifies potential competition concerns, it may issue a "second request" -- a formal demand for additional documents and information -- that typically adds months to deal timelines and imposes significant compliance costs. Prior to the Biden administration, the DOJ and the FTC routinely executed targeted second request investigations, entering into timing agreements with merging parties that prioritized the submission of information most relevant to the agencies' competitive concerns. After reviewing this priority information, the reviewing agency could close its investigation, modify or narrow the second request, or require full compliance.
The Biden administration moved away from this targeted approach in favor of broader investigations. The Biden-era FTC also adopted sweeping changes to the HSR notification form that roughly tripled average preparation time, but those amended rules were subsequently vacated by the Eastern District of Texas. Merging parties currently file under the pre-2025 form while the agencies solicit public comment on a revised HSR form.
The Announcement
Associate Attorney General Stanley E. Woodward Jr. framed the return to targeted reviews as an effort "to eliminate bureaucratic burdens while still preserving the integrity of second request investigations." He further stated the change "will allow for quicker and more efficient review of proposed transactions; more effective use of taxpayer resources; and above all, helps the [DOJ] do its job to safeguard a competitive marketplace while keeping America open for business."
The model timing agreement outlines the mechanics of the targeted process. Under the agreement, the parties commit to an expedited production of "priority" documents and information the DOJ has identified as most pertinent to resolving its competitive questions. Following review of the priority production, the DOJ will notify the parties whether it intends to: (1) close the investigation or grant early termination; (2) modify or narrow the second request; or (3) proceed with the investigation and require full compliance with the original second request.
Importantly, the DOJ emphasized that it "remains open to good faith negotiations regarding modifications to second requests in all cases" and "will continue to require full compliance in circumstances in which broader information is necessary to reach an enforcement decision."
While this announcement applies only to the DOJ, the FTC Chair Andrew Ferguson has signaled a broadly aligned philosophy, stating the FTC "must get out of the way quickly" when a merger does not violate antitrust laws "to avoid bogging down innovation and interfering with the forces of a free and competitive market."
M&A Enforcement under the Trump Administration
This announcement is part of the Trump administration's broader approach to merger enforcement. The current administration has consistently signaled its preference for reducing procedural hurdles on deal parties while not materially decreasing antitrust enforcement activity.
Enforcement by the Numbers
The recently released FY2025 HSR Annual Report, covering October 2024 through September 2025, provides a useful snapshot of the transition between administrations. The agencies issued 41 second requests in FY2025, representing 2.1% of notified transactions -- a slight decrease from FY2024's 3.0% rate but consistent with the long-standing average of approximately 2-3%. Total merger enforcement actions dropped from 32 in FY2024 to 18 in FY2025.
Return of Consent Decrees
The early dip in enforcement actions may reflect the second Trump administration's preference for settlement. During the Biden administration, agencies strongly favored litigation to block deals rather than negotiated settlements. The second Trump administration has returned to accepting structural remedies (e.g., divestitures) and behavioral commitments as the primary tools for resolving competition concerns.
Broader Themes
The second Trump administration also has articulated an "America first" antitrust framework, with enforcement priorities oriented toward protecting workers, consumers, small businesses, and US manufacturing. Industries in the crosshairs of the administration's policy priorities -- such as agriculture, health care, labor, technology, and manufacturing -- continue to draw focused scrutiny, while the agencies have signaled greater willingness to clear transactions quickly in other sectors.
Implications for Transacting Parties
For companies contemplating M&A transactions during the remainder of the second Trump administration, we note the following practical considerations.
Reduced Second Request Timelines and Costs
Parties that receive a second request from the DOJ should anticipate greater willingness to negotiate the scope of production, prioritize targeted submissions, and engage in constructive dialogue about the DOJ's competitive concerns. This should translate into shorter investigations and lower compliance costs for many transactions.
Proactive Engagement Remains Critical
The availability of a targeted process places a premium on early and substantive engagement with the DOJ. Parties and their counsel should be prepared to identify and address the DOJ's likely competition concerns proactively, offering to prioritize relevant information to facilitate a more efficient review. For high-profile or politically sensitive transactions, companies also should consider developing a broader engagement strategy that accounts for the White House's increasingly direct role in antitrust enforcement decisions during this administration.
State Enforcement May Intensify
Companies also should be mindful that state attorneys general may seek to fill any perceived gaps in federal enforcement. Multiple states have enacted or expanded their own premerger notification regimes, and multistate coalitions have shown a willingness to investigate and prosecute transactions independently of -- and at times in opposition to -- the enforcement decisions of federal authorities.
In Conclusion
The antitrust laws are nuanced and complex and their application to specific transactions is fact sensitive. We strongly recommend that companies contemplating a merger or acquisition consult with experienced antitrust and HSR counsel early in the deal process to navigate the current regulatory landscape and develop an effective engagement strategy.
* * *
The material contained in this communication is informational, general in nature and does not constitute legal advice. The material contained in this communication should not be relied upon or used without consulting a lawyer to consider your specific circumstances. This communication was published on the date specified and may not include any changes in the topics, laws, rules or regulations covered. Receipt of this communication does not establish an attorney-client relationship. In some jurisdictions, this communication may be considered attorney advertising.
* * *
Meet the Authors
Anna M. Behrmann
Counsel
Indianapolis
+1 317 237 1016
anna.behrmann@faegredrinker.com
* * *
Kathy L. Osborn
Partner
Indianapolis
+1 317 237 8261
kathy.osborn@faegredrinker.com
* * *
Matthew R. Levy
Partner
Indianapolis
+1 317 237 1114
matthew.levy@faegredrinker.com
* * *
Mihajlo Gasic
Associate
Chicago
+1 312 569 1142
mihajlo.gasic@faegredrinker.com
* * *
Original text here: https://www.faegredrinker.com/en/insights/publications/2026/7/doj-returns-to-targeted-second-request-investigations-publishes-model-timing-agreement
[Category: BizLaw/Legal]
Expert Vision: How a GE Vernova Engineer Uses AI to See the Invisible
CAMBRIDGE, Massachusetts, July 28 -- G.E. Vernova, an energy company, posted the following news release:
* * *
Expert Vision: How a GE Vernova Engineer Uses AI to See the Invisible
As the global energy transition accelerates, maintaining the long-term stamina of critical infrastructure like wind turbines requires being able to spot hidden risks before they can become failures. Proactively protecting these systems means uninterrupted energy for neighborhoods, smarter and safer environments for inspectors, and lower operational costs. Yet inspecting a wind-turbine blade 100 meters in length -- ... Show Full Article CAMBRIDGE, Massachusetts, July 28 -- G.E. Vernova, an energy company, posted the following news release: * * * Expert Vision: How a GE Vernova Engineer Uses AI to See the Invisible As the global energy transition accelerates, maintaining the long-term stamina of critical infrastructure like wind turbines requires being able to spot hidden risks before they can become failures. Proactively protecting these systems means uninterrupted energy for neighborhoods, smarter and safer environments for inspectors, and lower operational costs. Yet inspecting a wind-turbine blade 100 meters in length --longer than the wingspan of a commercial airplane -- to find tiny flaws or stress points that could weaken it is a daunting task. Where would you begin?
Until recently, this job was done manually, by technicians relying on intense attention to detail. One person would walk through the interior of the blade with a high-powered flashlight, recording detailed images. Others would painstakingly scroll through the resulting data, checking for any deviation from exacting requirements. The concentration needed was so demanding that a technician would have to take a break every 25 minutes to avoid losing focus. From start to finish, an inspection could take up to 15 hours.
There was a clear opportunity to improve the process, making it more efficient while heightening accuracy. Sivaramanivas Ramaswamy specializes in such challenges. For more than two decades, Ramaswamy, a senior engineer with GE Vernova's Advanced Research Center in Bengaluru, India, has been developing techniques to see hidden problems before they become disruptions. He is an expert in nondestructive evaluation -- technologies that detect hidden damage without cutting equipment open. Using ultrasound, terahertz waves, and other tools that send signals into materials and read the echoes, his work gives engineers entirely new ways to see inside complex machinery without taking it apart.
"I say to my friends that I work on failures," says Ramaswamy, whose team received a tech award in 2024 from GE Vernova for the new inspection process, known as the Digital Blade Certificate. "When you image a crack with all its details, you don't get the same joy as when you see the face of an unborn baby on ultrasonic images. But it does still give me a high when I'm able to see something that's not possible with your naked eyes."
Working with the global team in Bengaluru and Niskayuna, New York, Ramaswamy helped develop this digital inspection protocol for wind turbine blades. Today, small machines known as crawlers capture images in areas inside the blades that are inaccessible to human inspectors. An AI-powered model scans the images for anomalies, flagging features such as cracks, gaps, or weak bonds. Human technicians then review the most critical areas, balancing automation with human judgment. Ramaswamy now is improving the process by experimenting with an AI model trained on ultrasound images.
Adapting Cross-Industry Technologies for Advanced Inspection
As a university student, Ramaswamy developed expertise in nondestructive evaluation by learning fields such as electronics, computer science, and mechanical engineering. After working in aerospace for the Indian government, the opportunity to tackle broad research questions drew him to GE Vernova.
In addition to the wind industry, early in Ramaswamy's career, there was a "continuous back-and-forth between different teams" in the gas power sector as well as aerospace and healthcare, Ramaswamy says. "At first, it looks like these domains don't have anything in common, but at the heart of the technology there is a commonality. The multidisciplinary element is core to nondestructive evaluation, and working at GE Vernova keeps me motivated."
Ramaswamy frequently adapts technologies from one industry to solve problems in another. For example, he has helped modify laser-based terahertz inspection tools, already used in automotive and aerospace, for the extreme conditions of gas turbines. These systems use femtosecond laser-generated signals to probe a material's subsurface, measuring microscopic coating thicknesses and detecting hidden defects.
His team also is exploring millimeter-wave technologies -- high-frequency radar systems similar to the sensors used in autonomous vehicles, that can effectively see through solid structures. Early field trials in wind energy suggest these tools could expand how engineers inspect critical infrastructure, allowing them to spot failures before they occur.
Stopping Failures Before They Start: AI and Digital Twins
The next challenge for Ramaswamy is to not just uncover problems that have already surfaced, but to predict potential failure points before they happen. He is working on building digital twins -- virtual models that combine sensor data with AI to show how parts wear down over time and forecast where failures are most likely to occur. He and his team have deployed this approach in Southeast Asia at two power plants that contain up to 350 miles of tubes, which are time-consuming to inspect and are subject to significant heat and pressure. If a tube ruptures anywhere, the resulting outage can take weeks to repair. Predicting where this might happen makes preventive maintenance possible.
While his interests are wide-ranging, Ramaswamy's innovations help build equipment that lasts longer and is easier to maintain, ultimately bringing down the cost of power generation and helping to keep the lights on for households around the world. While most people will never see his work behind the scenes, his work helps pave the way for fewer unexpected outages, less downtime, safer inspections, and more reliable power for homes, hospitals, businesses, and grids.
"I still see myself as a student," he says. "Even now, if I get an opportunity to meet a new customer or travel to a new site, I keep doing it as part of my learning exercise. There can be a million ideas on the table, but there are only a few that really help the customer. Working at GE Vernova helps me to identify those few that are critical."
* * *
Original text here: https://www.gevernova.com/news/articles/expert-vision-how-ge-vernova-engineer-uses-ai-see-invisible
[Category: BizEnergy]
* * *
Expert Vision: How a GE Vernova Engineer Uses AI to See the Invisible
As the global energy transition accelerates, maintaining the long-term stamina of critical infrastructure like wind turbines requires being able to spot hidden risks before they can become failures. Proactively protecting these systems means uninterrupted energy for neighborhoods, smarter and safer environments for inspectors, and lower operational costs. Yet inspecting a wind-turbine blade 100 meters in length -- ... Show Full Article CAMBRIDGE, Massachusetts, July 28 -- G.E. Vernova, an energy company, posted the following news release: * * * Expert Vision: How a GE Vernova Engineer Uses AI to See the Invisible As the global energy transition accelerates, maintaining the long-term stamina of critical infrastructure like wind turbines requires being able to spot hidden risks before they can become failures. Proactively protecting these systems means uninterrupted energy for neighborhoods, smarter and safer environments for inspectors, and lower operational costs. Yet inspecting a wind-turbine blade 100 meters in length --longer than the wingspan of a commercial airplane -- to find tiny flaws or stress points that could weaken it is a daunting task. Where would you begin?
Until recently, this job was done manually, by technicians relying on intense attention to detail. One person would walk through the interior of the blade with a high-powered flashlight, recording detailed images. Others would painstakingly scroll through the resulting data, checking for any deviation from exacting requirements. The concentration needed was so demanding that a technician would have to take a break every 25 minutes to avoid losing focus. From start to finish, an inspection could take up to 15 hours.
There was a clear opportunity to improve the process, making it more efficient while heightening accuracy. Sivaramanivas Ramaswamy specializes in such challenges. For more than two decades, Ramaswamy, a senior engineer with GE Vernova's Advanced Research Center in Bengaluru, India, has been developing techniques to see hidden problems before they become disruptions. He is an expert in nondestructive evaluation -- technologies that detect hidden damage without cutting equipment open. Using ultrasound, terahertz waves, and other tools that send signals into materials and read the echoes, his work gives engineers entirely new ways to see inside complex machinery without taking it apart.
"I say to my friends that I work on failures," says Ramaswamy, whose team received a tech award in 2024 from GE Vernova for the new inspection process, known as the Digital Blade Certificate. "When you image a crack with all its details, you don't get the same joy as when you see the face of an unborn baby on ultrasonic images. But it does still give me a high when I'm able to see something that's not possible with your naked eyes."
Working with the global team in Bengaluru and Niskayuna, New York, Ramaswamy helped develop this digital inspection protocol for wind turbine blades. Today, small machines known as crawlers capture images in areas inside the blades that are inaccessible to human inspectors. An AI-powered model scans the images for anomalies, flagging features such as cracks, gaps, or weak bonds. Human technicians then review the most critical areas, balancing automation with human judgment. Ramaswamy now is improving the process by experimenting with an AI model trained on ultrasound images.
Adapting Cross-Industry Technologies for Advanced Inspection
As a university student, Ramaswamy developed expertise in nondestructive evaluation by learning fields such as electronics, computer science, and mechanical engineering. After working in aerospace for the Indian government, the opportunity to tackle broad research questions drew him to GE Vernova.
In addition to the wind industry, early in Ramaswamy's career, there was a "continuous back-and-forth between different teams" in the gas power sector as well as aerospace and healthcare, Ramaswamy says. "At first, it looks like these domains don't have anything in common, but at the heart of the technology there is a commonality. The multidisciplinary element is core to nondestructive evaluation, and working at GE Vernova keeps me motivated."
Ramaswamy frequently adapts technologies from one industry to solve problems in another. For example, he has helped modify laser-based terahertz inspection tools, already used in automotive and aerospace, for the extreme conditions of gas turbines. These systems use femtosecond laser-generated signals to probe a material's subsurface, measuring microscopic coating thicknesses and detecting hidden defects.
His team also is exploring millimeter-wave technologies -- high-frequency radar systems similar to the sensors used in autonomous vehicles, that can effectively see through solid structures. Early field trials in wind energy suggest these tools could expand how engineers inspect critical infrastructure, allowing them to spot failures before they occur.
Stopping Failures Before They Start: AI and Digital Twins
The next challenge for Ramaswamy is to not just uncover problems that have already surfaced, but to predict potential failure points before they happen. He is working on building digital twins -- virtual models that combine sensor data with AI to show how parts wear down over time and forecast where failures are most likely to occur. He and his team have deployed this approach in Southeast Asia at two power plants that contain up to 350 miles of tubes, which are time-consuming to inspect and are subject to significant heat and pressure. If a tube ruptures anywhere, the resulting outage can take weeks to repair. Predicting where this might happen makes preventive maintenance possible.
While his interests are wide-ranging, Ramaswamy's innovations help build equipment that lasts longer and is easier to maintain, ultimately bringing down the cost of power generation and helping to keep the lights on for households around the world. While most people will never see his work behind the scenes, his work helps pave the way for fewer unexpected outages, less downtime, safer inspections, and more reliable power for homes, hospitals, businesses, and grids.
"I still see myself as a student," he says. "Even now, if I get an opportunity to meet a new customer or travel to a new site, I keep doing it as part of my learning exercise. There can be a million ideas on the table, but there are only a few that really help the customer. Working at GE Vernova helps me to identify those few that are critical."
* * *
Original text here: https://www.gevernova.com/news/articles/expert-vision-how-ge-vernova-engineer-uses-ai-see-invisible
[Category: BizEnergy]