News & Events

1,211 News items found.

Learn about the MERL Seminar Series.

  •  NEWS    MERL presents 9 papers at 2023 IFAC World Congress
    Date: July 9, 2023 - July 14, 2023
    MERL Contacts: Karl Berntorp; Scott A. Bortoff; Ankush Chakrabarty; Stefano Di Cairano; Christopher R. Laughman; Diego Romeres; Abraham P. Vinod
    Research Areas: Control, Dynamical Systems, Machine Learning, Multi-Physical Modeling, Optimization, Robotics
    • MERL researchers presented 9 papers and organized 2 invited/workshop sessions at the 2023 IFAC World Congress held in Yokohama, JP.

      MERL's contributions covered topics including decision-making for autonomous vehicles, statistical and learning-based estimation for GNSS and energy systems, impedance control for delta robots, learning for system identification of rigid body dynamics and time-varying systems, and meta-learning for deep state-space modeling using data from similar systems. The invited session (MERL co-organizer: Ankush Chakrabarty) was on the topic of “Estimation and observer design: theory and applications” and the workshop (MERL co-organizer: Karl Berntorp) was on “Gaussian Process Learning for Systems and Control”.
  •  NEWS    MERL researchers present 3 papers on Dexterous Manipulation at RSS 23.
    Date: July 11, 2023
    Where: Daegu, Korea
    MERL Contacts: Siddarth Jain; Devesh K. Jha; Arvind Raghunathan
    Research Areas: Artificial Intelligence, Machine Learning, Robotics
    • MERL researchers presented 3 papers at the 19th edition of Robotics:Science and Systems Conference in Daegu, Korea. RSS is the flagship conference of the RSS foundation and is run as a single track conference presenting a limited number of high-quality papers. This year the main conference had a total of 112 papers presented. MERL researchers presented 2 papers in the main conference on planning and perception for dexterous manipulation. Another paper was presented in a workshop of learning for dexterous manipulation. More details can be found here
  •  NEWS    Keynote address given by Philip Orlik at 9th annual IEEE Smartcomp conference
    Date: June 26, 2023
    Where: International Conference on Smart Computing (SMARTCOMP), Vanderbilt University, Nashville, Tennessee
    MERL Contact: Philip V. Orlik
    Research Areas: Communications, Dynamical Systems, Machine Learning, Multi-Physical Modeling, Signal Processing
    • VP & Research Director, Philip Orlik, gave a keynote titled, "Smart Technologies for Smarter Buildings" at the 9th edition of the IEEE International Conference on Smart Computing (SMARTCOMP) focusing on some of the research challenges and opportunities that arise as we seek to achieve net-zero emissions in Smart building environments.

      SMARTCOMP is the premier conference on smart computing. Smart computing is a multidisciplinary domain based on the synergistic influence of advances in sensor-based technologies, Internet of Things, cyber-physical systems, edge computing, big data analytics, machine learning, cognitive computing, and artificial intelligence.
  •  NEWS    MERL researchers presenting four papers and co-organizing a workshop at CVPR 2023
    Date: June 18, 2023 - June 22, 2023
    Where: Vancouver/Canada
    MERL Contacts: Anoop Cherian; Michael J. Jones; Suhas Lohit; Kuan-Chuan Peng
    Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    • MERL researchers are presenting 4 papers and co-organizing a workshop at the CVPR 2023 conference, which will be held in Vancouver, Canada June 18-22. CVPR is one of the most prestigious and competitive international conferences in computer vision. Details are provided below.

      1. “Are Deep Neural Networks SMARTer than Second Graders,” by Anoop Cherian, Kuan-Chuan Peng, Suhas Lohit, Kevin Smith, and Joshua B. Tenenbaum

      We present SMART: a Simple Multimodal Algorithmic Reasoning Task and the associated SMART-101 dataset for evaluating the abstraction, deduction, and generalization abilities of neural networks in solving visuo-linguistic puzzles designed for children in the 6-8 age group. Our experiments using SMART-101 reveal that powerful deep models are not better than random accuracy when analyzed for generalization. We also evaluate large language models (including ChatGPT) on a subset of SMART-101 and find that while these models show convincing reasoning abilities, their answers are often incorrect.


      2. “EVAL: Explainable Video Anomaly Localization,” by Ashish Singh, Michael J. Jones, and Erik Learned-Miller

      This work presents a method for detecting unusual activities in videos by building a high-level model of activities found in nominal videos of a scene. The high-level features used in the model are human understandable and include attributes such as the object class and the directions and speeds of motion. Such high-level features allow our method to not only detect anomalous activity but also to provide explanations for why it is anomalous.


      3. "Aligning Step-by-Step Instructional Diagrams to Video Demonstrations," by Jiahao Zhang, Anoop Cherian, Yanbin Liu, Yizhak Ben-Shabat, Cristian Rodriguez, and Stephen Gould

      The rise of do-it-yourself (DIY) videos on the web has made it possible even for an unskilled person (or a skilled robot) to imitate and follow instructions to complete complex real world tasks. In this paper, we consider the novel problem of aligning instruction steps that are depicted as assembly diagrams (commonly seen in Ikea assembly manuals) with video segments from in-the-wild videos. We present a new dataset: Ikea Assembly in the Wild (IAW) and propose a contrastive learning framework for aligning instruction diagrams with video clips.


      4. "HaLP: Hallucinating Latent Positives for Skeleton-Based Self-Supervised Learning of Actions," by Anshul Shah, Aniket Roy, Ketul Shah, Shlok Kumar Mishra, David Jacobs, Anoop Cherian, and Rama Chellappa

      In this work, we propose a new contrastive learning approach to train models for skeleton-based action recognition without labels. Our key contribution is a simple module, HaLP: Hallucinating Latent Positives for contrastive learning. HaLP explores the latent space of poses in suitable directions to generate new positives. Our experiments using HaLP demonstrates strong empirical improvements.


      The 4th Workshop on Fair, Data-Efficient, and Trusted Computer Vision

      MERL researcher Kuan-Chuan Peng is co-organizing the fourth Workshop on Fair, Data-Efficient, and Trusted Computer Vision ( in conjunction with CVPR 2023 on June 18, 2023. This workshop provides a focused venue for discussing and disseminating research in the areas of fairness, bias, and trust in computer vision, as well as adjacent domains such as computational social science and public policy.
  •  NEWS    Mitsubishi Electric Corporation Press Release Announces Worlds First GaN Power Amplifier Capable of Wideband Operation for 4G, 5G and Beyond 5G/6G.
    Date: June 8, 2023
    MERL Contacts: Toshiaki Koike-Akino; Koon Hoo Teo
    Research Areas: Communications, Electronic and Photonic Devices, Machine Learning, Signal Processing
    • Mitsubishi Electric Corporation announced today it has developed what is believed to be the world's first gallium nitride (GaN) power amplifier that achieves a frequency range of 3,400MHz using a single power amplifier, which the company has demonstrated can be used for 4G, 5G and Beyond 5G/6G communication systems operating at different frequencies in a single base station. The amplifier is expected to enable the radio unit (transceiver) to be shared with different communication systems and lead to more power-efficient base stations.

      Mitsubishi Electric Researchers, Toshiaki Koike-Akino and Koon Hoo Teo helped developed the technology and device. Technical details will be presented at the IEEE International Microwave Symposium 2023 this month.

      Please see the link below for the full press release from Mitsubishi Electric.
  •  NEWS    Abraham Vinod gave an invited talk at the University of California Santa Cruz
    Date: June 8, 2023
    Where: Zoom
    MERL Contact: Abraham P. Vinod
    Research Areas: Artificial Intelligence, Control, Dynamical Systems, Optimization, Robotics
    • Abraham Vinod gave an invited talk at the Electrical and Computer Engineering Department, the University of California Santa Cruz, titled "Motion Planning under Constraints and Uncertainty using Data and Reachability". His presentation covered recent work on fast and safe motion planners that can allow for coordination among agents, mitigate uncertainty arising from sensing limitations and simplified models, and tolerate the possibility of failures.
  •  NEWS    Ankush Chakrabarty co-organized three sessions at the ACC2023, and was nominated for Best Energy Systems Paper.
    Date: June 30, 2023 - June 2, 2023
    Where: San Diego, CA
    MERL Contact: Ankush Chakrabarty
    Research Areas: Applied Physics, Artificial Intelligence, Control, Data Analytics, Dynamical Systems, Machine Learning, Multi-Physical Modeling, Optimization, Robotics
    • Ankush Chakrabarty (researcher, Multiphysical Systems Team) co-organized and spoke at 3 sessions at the 2023 American Control Conference in San Diego, CA. These include: (1) A tutorial session (w/ Stefano Di Cairano) on "Physics Informed Machine Learning for Modeling and Control": an effort with contributions from multiple academic institutes and US research labs; (2) An invited session on "Energy Efficiency in Smart Buildings and Cities" in which his paper (w/ Chris Laughman) on "Local Search Region Constrained Bayesian Optimization for Performance Optimization of Vapor Compression Systems" was nominated for Best Energy Systems Paper Award; and, (3) A special session on Diversity, Equity, and Inclusion to improve recruitment and retention of underrepresented groups in STEM research.
  •  NEWS    Abraham Vinod serves as a panelist at the Student Networking Event at American Control Conference 2023
    Date: June 1, 2023
    Where: San Diego, CA
    MERL Contact: Abraham P. Vinod
    Research Areas: Control, Optimization
    • The student networking event provides an opportunity for all interested students attending American Control Conference 2023 to receive career advice from professionals working in industry, academia, and national laboratories during a structured event. The event aims to provide an engaging experience to students that illustrates the benefits of involvement in the control community and encourage their continued participation as the future leaders in the field.
  •  NEWS    MERL researchers present 10 papers at the American Control Conference (ACC)
    Date: May 31, 2023 - June 2, 2023
    Where: San Diego, CA
    MERL Contacts: Karl Berntorp; Ankush Chakrabarty; Vedang M. Deshpande; Stefano Di Cairano; Marcus Greiff; Devesh K. Jha; Christopher R. Laughman; Rien Quirynen; Arvind Raghunathan; Diego Romeres; Abraham P. Vinod; Yebin Wang; Avishai Weiss
    Research Areas: Control, Machine Learning, Optimization
    • MERL will present 10 papers at the American Control Conference (ACC) in San Diego, CA, with topics including autonomous-vehicle decision making and control, physics-informed machine learning, motion planning, control subject to nonconvex chance constraints, and optimal power management. Two talks are part of tutorial sessions.
      MERL will also be present at the conference as a sponsor, with a booth for discussing with researchers and students, and hosting a special session at lunch with highlights of MERL research and work philosophy.
  •  NEWS    MERL Researchers Organize Two MiniSymposia and Five Invited Talks at the 2023 SIAM Conference on Optimization
    Date: May 31, 2023 - June 3, 2023
    Where: 2023 SIAM Conference on Optimization
    MERL Contacts: Devesh K. Jha; Arvind Raghunathan
    Research Areas: Control, Optimization, Robotics
    • Arvind Raghunathan, Senior Team Leader and Senior Principal Research Scientist in Optimization & Intelligent Robotics team, will organize two minisymposia at the 2023 SIAM Conference on Optimization to be held in Seattle from May 31 to June 3. The two minisymposia titled "Optimization in Control – Algorithms, Applications, and Software" and "New Algorithmic Techniques for Global Optimization" will feature twelve invited speakers from academia and national labs.

      Additionally, Arvind together with Devesh Jha, Principal Research Scientist in Optimization & Intelligent Robotics Team, and collaborators will present five invited talks covering the topics of algorithms for convex programs, multilinear programs, mixed-integer nonlinear programs, and robotics.

  •  NEWS    MERL Researchers Present Thirteen Papers at the 2023 IEEE International Conference on Robotics and Automation (ICRA)
    Date: May 29, 2023 - June 2, 2023
    Where: 2023 IEEE International Conference on Robotics and Automation (ICRA)
    MERL Contacts: Anoop Cherian; Radu Corcodel; Siddarth Jain; Devesh K. Jha; Toshiaki Koike-Akino; Tim K. Marks; Daniel N. Nikovski; Arvind Raghunathan; Diego Romeres
    Research Areas: Computer Vision, Machine Learning, Optimization, Robotics
    • MERL researchers will present thirteen papers, including eight main conference papers and five workshop papers, at the 2023 IEEE International Conference on Robotics and Automation (ICRA) to be held in London, UK from May 29 to June 2. ICRA is one of the largest and most prestigious conferences in the robotics community. The papers cover a broad set of topics in Robotics including estimation, manipulation, vision-based object recognition and segmentation, tactile estimation and tool manipulation, robotic food handling, robot skill learning, and model-based reinforcement learning.

      In addition to the paper presentations, MERL robotics researchers will also host an exhibition booth and look forward to discussing our research with visitors.
  •  NEWS    MERL researchers presented four papers and organized a special session at The 14th IEEE International Electric Machines and Drives Conference
    Date: May 15, 2023 - May 18, 2023
    Where: San Francisco, CA
    MERL Contacts: Dehong Liu; Bingnan Wang
    Research Areas: Applied Physics, Control, Electric Systems, Machine Learning, Optimization, Signal Processing
    • MERL researchers Yusuke Sakamoto, Anantaram Varatharajan, and
      Bingnan Wang presented four papers at IEMDC 2023 held May 15-18 in San Francisco, CA. The topics of the four oral presentations range from electric machine design optimization, to fault detection and sensorless control. Bingnan Wang organized a special session at the conference entitled: Learning-based Electric Machine Design and Optimization. Bingnan Wang and Yusuke Sakamoto together chaired the special session, as well as a session on: Condition Monitoring, Fault Diagnosis and Prognosis.

      The 14th IEEE International Electric Machines and Drives Conference: IEMDC 2023, is one of the major conferences in the area of electric machines and drives. The conference was established in 1997 and has taken place every two years thereafter.
  •  NEWS    Arvind Raghunathan to Chair The 2022 Howard Rosenbrock Prize Committee
    Date: April 30, 2023
    MERL Contact: Arvind Raghunathan
    Research Area: Optimization
    • Arvind Raghunathan, Senior Team Leader and Senior Principal Research Scientist with Optimization and Intelligent Robotics team, will serve as the Chair of The 2022 Howard Rosenbrock Prize Committee. Every year, Optimization and Engineering (OPTE) journal honors excellence in scientific research by presenting the Rosenbrock Prize to the best paper published in the previous year. The prize recognizes outstanding research contributions that demonstrate Howard Rosenbrock’s own dedication to bridging the gap between optimization and engineering.
  •  NEWS    Anthony Vetro appointed President & CEO of Mitsubishi Electric Research Laboratories
    Date: April 1, 2023
    MERL Contact: Anthony Vetro
    • Anthony Vetro has been appointed President and Chief Executive Officer (CEO) of Mitsubishi Electric Research Laboratories (MERL), the research and development arm for Mitsubishi Electric Corporation in the U.S. In his role, Vetro will oversee all aspects of the lab’s operations; manage and direct its long-term goals, growth and return on investment; and collaborate closely with Mitsubishi Electric’s research counterparts in Japan on advancing the company’s global smart society and sustainability initiatives.

      Vetro previously served as Vice President & Director of MERL. In this role, he contributed to the strategic direction of the company where he established new research programs and led teams in a variety of emerging technology areas. He succeeds Richard C. Waters, a founding MERL member, who was CEO for 24 years, and will continue as chairperson.

      “Anthony has played a significant role in shaping MERL’s evolution as a premier research lab that drives innovation across all of our U.S. business units,” said Mike Corbo, chief representative for the America’s region. “His leadership will further advance our long-term vision to integrate our cross-industry products, services and technologies, and enable the interconnection of people-centric technology and systems that will help realize a truly sustainable smart society.”

      Vetro began his MERL career in 1996, where he conducted research in the area of multimedia signal processing, with a focus on video compression. His research contributed to the transfer and development of several technologies that were integrated into Mitsubishi Electric products, including digital television receivers and displays, surveillance and camera monitoring systems, automotive equipment, as well as satellite imaging systems. He holds a Ph.D. in electrical engineering from New York University – Tandon School of Engineering and is an IEEE Fellow.

      “MERL celebrated its 30th Anniversary last year, where we recognized our many innovations and the people that made them possible,” said Vetro. “I’m looking forward to working even more closely with our teams to further strengthen relationships among our business units and serve as technological bridge for product innovation throughout the next 30 years and beyond.”
  •  NEWS    Jonathan Le Roux gives invited talk at CMU's Language Technology Institute Colloquium
    Date: December 9, 2022
    Where: Pittsburg, PA
    MERL Contact: Jonathan Le Roux
    Research Areas: Artificial Intelligence, Machine Learning, Speech & Audio
    • MERL Senior Principal Research Scientist and Speech and Audio Senior Team Leader, Jonathan Le Roux, was invited by Carnegie Mellon University's Language Technology Institute (LTI) to give an invited talk as part of the LTI Colloquium Series. The LTI Colloquium is a prestigious series of talks given by experts from across the country related to different areas of language technologies. Jonathan's talk, entitled "Towards general and flexible audio source separation", presented an overview of techniques developed at MERL towards the goal of robustly and flexibly decomposing and analyzing an acoustic scene, describing in particular the Speech and Audio Team's efforts to extend MERL's early speech separation and enhancement methods to more challenging environments, and to more general and less supervised scenarios.
  •  NEWS    Rien Quirynen Appointed IPC Vice-Chair for the 8th IFAC Conference on NMPC 2024
    Date: August 27, 2024 - August 30, 2024
    Where: Kyoto, Japan
    MERL Contact: Rien Quirynen
    Research Areas: Control, Machine Learning, Multi-Physical Modeling, Optimization, Robotics
    • MERL researcher Rien Quirynen has been appointed as Vice-Chair from Industry of the International Program Committee of the 8th IFAC Conference on Nonlinear Model Predictive Control, which will be held in Kyoto, Japan, in August 2024.

      IFAC NMPC is the main symposium focused on model predictive control, theory, methods and applications, includes contributions on control, optimization, and machine learning research, and is held every 3 years.
  •  NEWS    Chris Laughman delivered two seminar talks for at the School of Engineering at Penn State
    Date: February 16, 2023 - February 17, 2023
    Where: Pennsylvania State University
    MERL Contact: Christopher R. Laughman
    Research Areas: Control, Machine Learning, Multi-Physical Modeling
    • On February 16 and 17, Chris Laughman, Senior Team Leader of the Multiphysical Systems Team, presented lectures for the Systems, Robotics, and Controls Seminar Series in the School of Engineering, and for the Distinguished Speaker Series in Architectural Engineering. His talk was titled "Architectural Thermofluid Systems: Next-Generation Challenges and Opportunities," and described characteristics of these systems that require specific attention in model-based system engineering processes, as well as MERL research to address these challenges.
  •  NEWS    Anthony Vetro participates in CES panel on renewable energy
    Date: January 7, 2023
    Where: Las Vegas, NV
    MERL Contact: Anthony Vetro
    • Sustainability took center stage at the 2023 Consumer Electronics Show held in Las Vegas from Jan 5-8. Anthony Vetro, VP & Director at MERL, participated in a panel on "Renewable Energy, Renewable World" at CES 2023, where he spoke on renewable energy solutions including electric vehicles, energy resource management, and energy-efficient heat pumps.

      The panel was moderated by Hayden Fields, Senior Reporter at Morning Brew. Other panelists included Andrea Murphy (Director of Environmental Affairs and Sustainability, Panasonic) Enass Abo-Hamed (CEO, H2GO Power), and Giovanni Fili (Founder and CEO, Exeger).

      The video recording of the panel is available online:
      CES 2023 Panel on Renewable Energy, Renewable World

      Related article on sustainability panels at CES:
  •  NEWS    Jianlin Guo recently delivered an invited talk at 2022 6th International Conference on Intelligent Manufacturing and Automation Engineering
    Date: December 15, 2022 - December 17, 2022
    MERL Contacts: Jianlin Guo; Philip V. Orlik; Kieran Parsons
    Research Areas: Artificial Intelligence, Data Analytics, Machine Learning
    • The performance of manufacturing systems is heavily affected by downtime – the time period that the system halts production due to system failure, anomalous operation, or intrusion. Therefore, it is crucial to detect and diagnose anomalies to allow predictive maintenance or intrusion detection to reduce downtime. This talk, titled "Anomaly detection and diagnosis in manufacturing systems using autoencoder", focuses on tackling the challenges arising from predictive maintenance in manufacturing systems. It presents a structured autoencoder and a pre-processed autoencoder for accurate anomaly detection, as well as a statistical-based algorithm and an autoencoder-based algorithm for anomaly diagnosis.
  •  NEWS    Yebin Wang delivered an invited industry talk at the 1st IEEE Industrial Electronics Society Annual On-Line Conference
    Date: December 9, 2022 - December 11, 2022
    MERL Contact: Yebin Wang
    Research Areas: Communications, Control, Optimization
    • Future factory, in the era of industry 4.0, is characterized by autonomy, digital twin, and mass customization. This talk, titled "Future factory automation and cyber-physical system: an industrial perspective," focuses on tackling the challenges arising from mass customization, for example reconfigurable machine controller and material flow.
  •  NEWS    MERL Researchers gave a Tutorial Talk on Quantum Machine Learning for Sensing and Communications at IEEE GLOBECOM
    Date: December 8, 2022
    MERL Contacts: Toshiaki Koike-Akino; Pu (Perry) Wang
    Research Areas: Artificial Intelligence, Communications, Computational Sensing, Machine Learning, Signal Processing
    • On December 8, 2022, MERL researchers Toshiaki Koike-Akino and Pu (Perry) Wang gave a 3.5-hour tutorial presentation at the IEEE Global Communications Conference (GLOBECOM). The talk, titled "Post-Deep Learning Era: Emerging Quantum Machine Learning for Sensing and Communications," addressed recent trends, challenges, and advances in sensing and communications. P. Wang presented on use cases, industry trends, signal processing, and deep learning for Wi-Fi integrated sensing and communications (ISAC), while T. Koike-Akino discussed the future of deep learning, giving a comprehensive overview of artificial intelligence (AI) technologies, natural computing, emerging quantum AI, and their diverse applications. The tutorial was conducted remotely. MERL's quantum AI technology was partly reported in the recent press release (

      The IEEE GLOBECOM is a highly anticipated event for researchers and industry professionals in the field of communications. Organized by the IEEE Communications Society, the flagship conference is known for its focus on driving innovation in all aspects of the field. Each year, over 3,000 scientific researchers submit proposals for program sessions at the annual conference. The theme of this year's conference was "Accelerating the Digital Transformation through Smart Communications," and featured a comprehensive technical program with 13 symposia, various tutorials and workshops.
  •  NEWS    MERL's Quantum Machine Learning Technology Featured in Mitsubishi Electric Corporation Press Release
    Date: December 2, 2022
    MERL Contacts: Toshiaki Koike-Akino; Kieran Parsons; Pu (Perry) Wang; Ye Wang
    Research Areas: Artificial Intelligence, Computational Sensing, Machine Learning, Signal Processing, Human-Computer Interaction
    • Mitsubishi Electric Corporation announced its development of a quantum artificial intelligence (AI) technology that automatically optimizes inference models to downsize the scale of computation with quantum neural networks. The new quantum AI technology can be integrated with classical machine learning frameworks for diverse solutions.

      Mitsubishi Electric has confirmed that the technology can be incorporated in the world's first applications for terahertz (THz) imaging, Wi-Fi indoor monitoring, compressed sensing, and brain-computer interfaces. The technology is based on recent research by MERL's Connectivity & Information Processing team and Computational Sensing team.

      Mitsubishi Electric's new quantum machine learning (QML) technology realizes compact inference models by fully exploiting the enormous capacity of quantum computers to express exponentially larger-state space with the number of quantum bits (qubits). In a hybrid combination of both quantum and classical AI, the technology can compensate for limitations of classical AI to achieve superior performance while significantly downsizing the scale of AI models, even when using limited data.
  •  NEWS    MERL researchers presenting workshop papers at NeurIPS 2022
    Date: December 2, 2022 - December 8, 2022
    MERL Contacts: Matthew Brand; Toshiaki Koike-Akino; Jing Liu; Saviz Mowlavi; Kieran Parsons; Ye Wang
    Research Areas: Artificial Intelligence, Control, Dynamical Systems, Machine Learning, Signal Processing
    • In addition to 5 papers in recent news (, MERL researchers presented 2 papers at the NeurIPS Conference Workshop, which was held Dec. 2-8. NeurIPS is one of the most prestigious and competitive international conferences in machine learning.

      - “Optimal control of PDEs using physics-informed neural networks” by Saviz Mowlavi and Saleh Nabi

      Physics-informed neural networks (PINNs) have recently become a popular method for solving forward and inverse problems governed by partial differential equations (PDEs). By incorporating the residual of the PDE into the loss function of a neural network-based surrogate model for the unknown state, PINNs can seamlessly blend measurement data with physical constraints. Here, we extend this framework to PDE-constrained optimal control problems, for which the governing PDE is fully known and the goal is to find a control variable that minimizes a desired cost objective. We validate the performance of the PINN framework by comparing it to state-of-the-art adjoint-based optimization, which performs gradient descent on the discretized control variable while satisfying the discretized PDE.

      - “Learning with noisy labels using low-dimensional model trajectory” by Vasu Singla, Shuchin Aeron, Toshiaki Koike-Akino, Matthew E. Brand, Kieran Parsons, Ye Wang

      Noisy annotations in real-world datasets pose a challenge for training deep neural networks (DNNs), detrimentally impacting generalization performance as incorrect labels may be memorized. In this work, we probe the observations that early stopping and low-dimensional subspace learning can help address this issue. First, we show that a prior method is sensitive to the early stopping hyper-parameter. Second, we investigate the effectiveness of PCA, for approximating the optimization trajectory under noisy label information. We propose to estimate the low-rank subspace through robust and structured variants of PCA, namely Robust PCA, and Sparse PCA. We find that the subspace estimated through these variants can be less sensitive to early stopping, and can outperform PCA to achieve better test error when trained on noisy labels.

      - In addition, new MERL researcher, Jing Liu, also presented a paper entitled “CoPur: Certifiably Robust Collaborative Inference via Feature Purification" based on his previous work before joining MERL. His paper was elected as a spotlight paper to be highlighted in lightening talks and featured paper panel.
  •  NEWS    MERL Researchers Presented Six Papers at the 2022 IEEE Conference on Decision and Control (CDC’22)
    Date: December 6, 2022 - December 9, 2022
    Where: Cancún, Mexico
    MERL Contacts: Mouhacine Benosman; Karl Berntorp; Ankush Chakrabarty; Marcus Greiff; Devesh K. Jha; Arvind Raghunathan; Diego Romeres; Yebin Wang
    Research Areas: Control, Optimization
    • MERL researchers presented six papers at the Conference on Decision and Control that was held in Cancún, Mexico from December 6-9, 2022. The papers covered a broad range of topics in the areas of decision making and control, including Bayesian optimization, quadratic programming, solution of differential equations, distributed Kalman filtering, thermal monitoring of batteries, and closed-loop control optimization.
  •  NEWS    Karl Berntorp gave Spotlight Talk at CDC Workshop on Gaussian Process Learning-Based Control
    Date: December 5, 2022
    Where: Cancun, Mexico
    MERL Contact: Karl Berntorp
    Research Areas: Control, Machine Learning
    • Karl Berntorp was an invited speaker at the workshop on Gaussian Process Learning-Based Control organized at the Conference on Decision and Control (CDC) 2022 in Cancun, Mexico.

      The talk was part of a tutorial-style workshop aimed to provide insight into the fundamentals behind Gaussian processes for modeling and control and sketching some of the open challenges and opportunities using Gaussian processes for modeling and control. The talk titled ``Gaussian Processes for Learning and Control: Opportunities for Real-World Impact" described some of MERL's efforts in using Gaussian processes (GPs) for learning and control, with several application examples and discussing some of the key benefits and limitations with using GPs for learning-based control.