News & Events

87 News items, Awards, Events or Talks found.



Learn about the MERL Seminar Series.



  •  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
    Brief
    • 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.
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  •  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; Marcel Menner; Rien Quirynen; Arvind Raghunathan; Diego Romeres; Abraham P. Vinod; Yebin Wang; Avishai Weiss
    Research Areas: Control, Machine Learning, Optimization
    Brief
    • 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.
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  •  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
    Brief
    • 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.

      See:
      https://meetings.siam.org/sess/dsp_programsess.cfm?SESSIONCODE=76268
      https://meetings.siam.org/sess/dsp_programsess.cfm?SESSIONCODE=76269
      https://meetings.siam.org/sess/dsp_programsess.cfm?SESSIONCODE=76270
      https://meetings.siam.org/sess/dsp_programsess.cfm?SESSIONCODE=76256
      https://meetings.siam.org/sess/dsp_programsess.cfm?SESSIONCODE=75897
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  •  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; Kei Ota; Arvind Raghunathan; Diego Romeres
    Research Areas: Computer Vision, Machine Learning, Optimization, Robotics
    Brief
    • 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.
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  •  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; Yusuke Sakamoto; Anantaram Varatharajan; Bingnan Wang
    Research Areas: Applied Physics, Control, Electric Systems, Machine Learning, Optimization, Signal Processing
    Brief
    • 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.
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  •  NEWS    Arvind Raghunathan to Chair The 2022 Howard Rosenbrock Prize Committee
    Date: April 30, 2023
    MERL Contact: Arvind Raghunathan
    Research Area: Optimization
    Brief
    • 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.
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  •  TALK    [MERL Seminar Series 2023] Dr. Michael Muehlebach presents talk titled Learning and Dynamical Systems
    Date & Time: Tuesday, April 11, 2023; 11:00 AM
    Speaker: Michael Muehlebach, Max Planck Institute for Intelligent Systems
    MERL Host: Marcel Menner
    Research Areas: Control, Dynamical Systems, Machine Learning, Optimization, Robotics
    Abstract
    • The talk will be divided into two parts. The first part of the talk introduces a class of first-order methods for constrained optimization that are based on an analogy to non-smooth dynamical systems. The key underlying idea is to express constraints in terms of velocities instead of positions, which has the algorithmic consequence that optimizations over feasible sets at each iteration are replaced with optimizations over local, sparse convex approximations. This results is a simplified suite of algorithms and an expanded range of possible applications in machine learning. In the second part of my talk, I will present a robot learning algorithm for trajectory tracking. The method incorporates prior knowledge about the system dynamics and by optimizing over feedforward actions, the risk of instability during deployment is mitigated. The algorithm will be evaluated on a ping-pong playing robot that is actuated by soft pneumatic muscles.
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  •  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
    Brief
    • 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.
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  •  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
    Brief
    • 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.
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  •  AWARD    Arvind Raghunathan receives Roberto Tempo Best CDC Paper Award at 2022 IEEE Conference on Decision & Control (CDC)
    Date: December 8, 2022
    Awarded to: Arvind Raghunathan
    MERL Contact: Arvind Raghunathan
    Research Areas: Control, Optimization
    Brief
    • Arvind Raghunathan, Senior Principal Research Scientist in the Data Analytics group, received the IEEE Control Systems Society Roberto Tempo Best CDC Paper Award. The award was presented at the 2022 IEEE Conference on Decision & Control (CDC).

      The award is given annually in honor of Roberto Tempo, the 44th President of the IEEE Control Systems Society (CSS). The Tempo Award Committee selects the best paper from the previous year's CDC based on originality, potential impact on any aspect of control theory, technology, or implementation, and for the clarity of writing. This year's award committee was headed by Prof. Patrizio Colaneri, Politecnico di Milano. Arvind's paper was nominated for the award by Prof. Lorenz Biegler, Carnegie Mellon University, with supporting letters from Prof. Andreas Waechter, Northwestern University, and Prof. Victor Zavala, University of Wisconsin-Madison.
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  •  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
    Brief
    • 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.
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  •  EVENT    MERL's Virtual Open House 2022
    Date & Time: Monday, December 12, 2022; 1:00pm-5:30pm ET
    Location: Mitsubishi Electric Research Laboratories (MERL)/Virtual
    Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio, Digital Video
    Brief
    • Join MERL's virtual open house on December 12th, 2022! Featuring a keynote, live sessions, research area booths, and opportunities to interact with our research team. Discover who we are and what we do, and learn about internship and employment opportunities.
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  •  NEWS    Rien Quirynen to give an invited talk at the University of California Santa Cruz
    Date: November 14, 2022
    Where: Zoom
    MERL Contact: Rien Quirynen
    Research Areas: Control, Dynamical Systems, Optimization, Robotics
    Brief
    • Rien Quirynen will give an invited talk at the Electrical and Computer Engineering Department, University of California Santa Cruz on "Real-time Motion Planning and Predictive Control by Mixed-integer Programming for Autonomous Vehicles". The talk will present recent work on a tailored branch-and-bound method for real-time motion planning and decision making on embedded processing units, and recent results for two applications related to automated driving and traffic control.
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  •  NEWS    Avishai Weiss to give an invited talk at the University of Kentucky
    Date: November 11, 2022
    MERL Contact: Avishai Weiss
    Research Areas: Control, Dynamical Systems, Optimization
    Brief
    • Avishai Weiss will give an invited talk at the William Maxwell Reed Seminar Series, Mechanical and Aerospace Engineering Department, University of Kentucky on "Fail-Safe Spacecraft Rendezvous." The talk will present some recent developments at MERL on guaranteeing safe rendezvous trajectories that avoid colliding with the target in the event of thruster anomalies.
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  •  TALK    [MERL Seminar Series 2022] Prof. Ufuk Topcu presents talk titled Autonomous systems in the intersection of formal methods, learning, and control
    Date & Time: Wednesday, October 26, 2022; 1:00 PM
    Speaker: Ufuk Topcu, The University of Texas at Austin
    MERL Host: Abraham P. Vinod
    Research Areas: Control, Dynamical Systems, Optimization
    Abstract
    • Autonomous systems are emerging as a driving technology for countlessly many applications. Numerous disciplines tackle the challenges toward making these systems trustworthy, adaptable, user-friendly, and economical. On the other hand, the existing disciplinary boundaries delay and possibly even obstruct progress. I argue that the nonconventional problems that arise in designing and verifying autonomous systems require hybrid solutions in the intersection of learning, formal methods, and controls. I will present examples of such hybrid solutions in the context of learning in sequential decision-making processes. These results offer novel means for effectively integrating physics-based, contextual, or structural prior knowledge into data-driven learning algorithms. They improve data efficiency by several orders of magnitude and generalizability to environments and tasks that the system had not experienced previously.
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  •  NEWS    Stefano Di Cairano to give a public lecture on status and challenges of automotive driving at IEEE CSS Day
    Date: October 24, 2022
    Where: Online, 10/24/2022 9:00am (Eastern time)
    MERL Contact: Stefano Di Cairano
    Research Areas: Control, Dynamical Systems, Optimization, Robotics
    Brief
    • Dr. Stefano Di Cairano (Senior Team Leader at MERL) has been invited to give a public talk at the first IEEE CSS Day event on the status, challenges, and role of control in autonomous driving.

      The talk, titled "The Long Voyage Towards Autonomous Driving, with Control Systems as the Co-Pilot", will review some history of autonomous driving, some of the open challenges that control technology may help address, and the next steps towards full-autonomy. The talk is designed for a non-technical audience, to explain the role and impact of control in automated driving technology.
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  •  TALK    [MERL Seminar Series 2022] Prof. Gianmario Pellegrino presents talk titled Design, Identification and Simulation of PM Synchronous Machines for Traction
    Date & Time: Friday, October 14, 2022; 11:00 AM
    Speaker: Gianmario Pellegrino, Politecnico di Tornio, Italy
    MERL Host: Anantaram Varatharajan
    Research Areas: Electric Systems, Electronic and Photonic Devices, Multi-Physical Modeling, Optimization
    Abstract
    • This seminar presents a comprehensive design and simulation procedure for Permanent Magnet Synchronous Machines (PMSMs) for traction application. The design of heavily saturated traction PMSMs is a multidisciplinary engineering challenge that CAD software suites struggle to grasp, whereas design equations are way too approximated for the purpose. This tutorial will present the design toolchain of SyR-e, where magnetic and structural design equations are fast-FEA corrected for an insightful initial design, later FEA calibrated with free or commercial FEA tools. One e-motor will be designed from zero referring to the specs and size of the Tesla Model 3 rear-axle e-motor. The circuital model of one motor with inverter and discrete-time control will be automatically generated, in Simulink and PLECS, with accessible torque control source code, for simulation of healthy and faulty conditions, ready for real-time implementation (e.g. HiL).
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  •  TALK    A Tunable Control/Learning Framework for Autonomous Systems
    Date & Time: Thursday, October 13, 2022; 1:30pm-2:30pm
    Speaker: Prof. Shaoshuai Mou, Purdue University
    MERL Host: Yebin Wang
    Research Areas: Control, Machine Learning, Optimization
    Abstract
    • Modern society has been relying more and more on engineering advance of autonomous systems, ranging from individual systems (such as a robotic arm for manufacturing, a self-driving car, or an autonomous vehicle for planetary exploration) to cooperative systems (such as a human-robot team, swarms of drones, etc). In this talk we will present our most recent progress in developing a fundamental framework for learning and control in autonomous systems. The framework comes from a differentiation of Pontryagin’s Maximum Principle and is able to provide a unified solution to three classes of learning/control tasks, i.e. adaptive autonomy, inverse optimization, and system identification. We will also present applications of this framework into human-autonomy teaming, especially in enabling an autonomous system to take guidance from human operators, which is usually sparse and vague.
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  •  NEWS    Rien Quirynen gives invited talk at ELO-X Workshop on Embedded Optimization and Learning for Robotics and Mechatronics
    Date: October 10, 2022 - October 11, 2022
    Where: University of Freiburg, Germany
    MERL Contact: Rien Quirynen
    Research Areas: Control, Machine Learning, Optimization
    Brief
    • Rien Quirynen is an invited speaker at an international workshop on Embedded Optimization and Learning for Robotics and Mechatronics, which is organized by the ELO-X project at the University of Freiburg in Germany. This talk, entitled "Embedded learning, optimization and predictive control for autonomous vehicles", presents recent results from multiple projects at MERL that leverage embedded optimization, machine learning and optimal control for autonomous vehicles.

      This workshop is part of the ELO-X Fall School and Workshop. Invited external lecturers will present state-of-the-art techniques and applications in the field of Embedded Optimization and Learning. ELO-X is a Marie Curie Innovative Training Network (ITN) funded by the European Commission Horizon 2020 program.
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  •  NEWS    MERL launches Postdoctoral Research Fellow program
    Date: September 21, 2022
    MERL Contacts: Philip V. Orlik; Anthony Vetro
    Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio
    Brief
    • Mitsubishi Electric Research Laboratories (MERL) invites qualified postdoctoral candidates to apply for the position of Postdoctoral Research Fellow. This position provides early career scientists the opportunity to work at a unique, academically-oriented industrial research laboratory. Successful candidates will be expected to define and pursue their own original research agenda, explore connections to established laboratory initiatives, and publish high impact articles in leading venues. Please refer to our web page for further details.
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  •  NEWS    MERL researchers win ASME Energy Systems Technical Committee Best Paper Award at 2022 American Control Conference
    Date: June 8, 2022
    Where: 2022 American Control Conference
    MERL Contacts: Ankush Chakrabarty; Christopher R. Laughman
    Research Areas: Control, Machine Learning, Multi-Physical Modeling, Optimization
    Brief
    • Researchers from EPFL (Wenjie Xu, Colin Jones) and EMPA (Bratislav Svetozarevic), in collaboration with MERL researchers Ankush Chakrabarty and Chris Laughman, recently won the ASME Energy Systems Technical Committee Best Paper Award at the 2022 American Control Conference for their work on "VABO: Violation-Aware Bayesian Optimization for Closed-Loop Performance Optimization with Unmodeled Constraints" out of 19 nominations and 3 finalists. The paper describes a data-driven framework for optimizing the performance of constrained control systems by systematically re-evaluating how cautiously/aggressively one should explore the search space to avoid sustained, large-magnitude constraint violations while tolerating small violations, and demonstrates these methods on a physics-based model of a vapor compression cycle.
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  •  NEWS    MERL researchers presented 9 papers at the American Control Conference (ACC)
    Date: June 8, 2022 - June 10, 2022
    Where: Atlanta, GA
    MERL Contacts: Karl Berntorp; Scott A. Bortoff; Ankush Chakrabarty; Stefano Di Cairano; Christopher R. Laughman; Marcel Menner; Rien Quirynen; Abraham P. Vinod; Avishai Weiss
    Research Areas: Control, Machine Learning, Optimization
    Brief
    • At the American Control Conference in Atlanta, GA, MERL presented 9 papers on subjects including autonomous-vehicle decision making and motion planning, realtime Bayesian inference and learning, reference governors for hybrid systems, Bayesian optimization, and nonlinear control.
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  •  NEWS    Arvind Raghunathan's publication is Featured Article in the current issue of the INFORMS Journal on Computing
    Date: April 1, 2022
    Where: INFORMS Journal on Computing (https://pubsonline.informs.org/journal/ijoc)
    MERL Contact: Arvind Raghunathan
    Research Areas: Artificial Intelligence, Machine Learning, Optimization
    Brief
    • Arvind Raghunathan co-authored a publication titled "JANOS: An Integrated Predictive and Prescriptive Modeling Framework" which has been chosen as a Featured Article in the current issue of the INFORMS Journal on Computing. The article was co-authored with Prof. David Bergman, a collaborator of MERL and Teng Huang, a former MERL intern, among others.

      The paper describes a new software tool, JANOS, that integrates predictive modeling and discrete optimization to assist decision making. Specifically, the proposed solver takes as input user-specified pretrained predictive models and formulates optimization models directly over those predictive models by embedding them within an optimization model through linear transformations.
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  •  NEWS    Toshiaki Koike-Akino gave an invited lecture to USPTO on advanced photonics
    Date: May 4, 2022
    MERL Contact: Toshiaki Koike-Akino
    Research Areas: Artificial Intelligence, Communications, Electronic and Photonic Devices, Machine Learning, Optimization, Signal Processing
    Brief
    • Toshiaki Koike-Akino gave an invited lecture on advanced photonic devices at the United States Patent and Trademark Office (USPTO) Technology Fair on May 4, 2022. Topics of the lecture included the recent progress of applied artificial intelligence (AI) technologies for optical systems, nano-photonic devices, and quantum technology. During the 2-hour interactive online presentation, he lectured to more than 200 patent examiner participants.

      USPTO Tech Fair Organizer mentioned:
      "Thank you very much for representing Advanced Photonic Devices at this year’s Technology Center 2800 Virtual Tech Fair held May 4th, 2022. Tech Fair is an important part of the United States Patent and Trademark Office’s Patent Examiner Technical Training Program (PETTP). Having a scientifically well-trained examiner workforce and ensuring the quality, consistency, and reliability of issued patents are top priorities at the USPTO. The PETTP is designed to achieve those priorities by giving examiners direct access to technical experts who are willing to share their knowledge about prior art and industry standards for both emerging and established technologies. Experts like yourself help to maintain our high quality of patent examination by keeping examiners updated on technologies and innovations pertinent to their field of examination.
      We very much appreciate your efforts, time, and contributions."
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  •  TALK    [MERL Seminar Series 2022] Prof. Michael Posa presents talk titled Hybrid robotics and implicit learning
    Date & Time: Tuesday, May 3, 2022; 1:00 PM
    Speaker: Michael Posa, University of Pennsylvania
    MERL Host: Devesh K. Jha
    Research Areas: Control, Optimization, Robotics
    Abstract
    • Machine learning has shown incredible promise in robotics, with some notable recent demonstrations in manipulation and sim2real transfer. These results, however, require either an accurate a priori model (for simulation) or a large amount of data. In contrast, my lab is focused on enabling robots to enter novel environments and then, with minimal time to gather information, accomplish complex tasks. In this talk, I will argue that the hybrid or contact-driven nature of real-world robotics, where a robot must safely and quickly interact with objects, drives this high data requirement. In particular, the inductive biases inherent in standard learning methods fundamentally clash with the non-differentiable physics of contact-rich robotics. Focusing on model learning, or system identification, I will show both empirical and theoretical results which demonstrate that contact stiffness leads to poor training and generalization, leading to some healthy skepticism of simulation experiments trained on artificially soft environments. Fortunately, implicit learning formulations, which embed convex optimization problems, can dramatically reshape the optimization landscape for these stiff problems. By carefully reasoning about the roles of stiffness and discontinuity, and integrating non-smooth structures, we demonstrate dramatically improved learning performance. Within this family of approaches, ContactNets accurately identifies the geometry and dynamics of a six-sided cube bouncing, sliding, and rolling across a surface from only a handful of sample trajectories. Similarly, a piecewise-affine hybrid system with thousands of modes can be identified purely from state transitions. Time permitting, I'll discuss how these learned models can be deployed for control via recent results in real-time, multi-contact MPC.
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