Optimization
Efficient solutions to large-scale problems.
Much of MERL's research activity involves formulating scientific and engineering problems as optimizations, which can be solved in an efficient way. We have developed fundamental algorithms to better solve classic problems, such as quadratic programs and minimum-cost paths. Our work also involves developing theoretical bounds to understand performance limits.
Quick Links
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Researchers
Stefano
Di Cairano
Ankush
Chakrabarty
Arvind
Raghunathan
Toshiaki
Koike-Akino
Daniel N.
Nikovski
Christopher R.
Laughman
Philip V.
Orlik
Yebin
Wang
Ye
Wang
Kieran
Parsons
Devesh K.
Jha
Abraham P.
Vinod
Scott A.
Bortoff
Diego
Romeres
Matthew
Brand
Petros T.
Boufounos
Hassan
Mansour
Pu
(Perry)
WangJianlin
Guo
Avishai
Weiss
Hongbo
Sun
Vedang M.
Deshpande
Dehong
Liu
Hongtao
Qiao
Yanting
Ma
Saviz
Mowlavi
Yuki
Shirai
Bingnan
Wang
Gordon
Wichern
Purnanand
Elango
Chungwei
Lin
William S.
Yerazunis
Jinyun
Zhang
Abraham
Goldsmith
Wataru
Tsujita
Anoop
Cherian
Radu
Corcodel
Pedro
Miraldo
Joshua
Rapp
Alexander
Schperberg
Kenji
Inomata
Na
Li
Jing
Liu
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Awards
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AWARD MERL Researchers Win Best Workshop Poster Award at the 2023 IEEE International Conference on Robotics and Automation (ICRA) Date: June 2, 2023
Awarded to: Yuki Shirai, Devesh Jha, Arvind Raghunathan and Dennis Hong
MERL Contacts: Devesh K. Jha; Arvind Raghunathan; Yuki Shirai
Research Areas: Artificial Intelligence, Optimization, RoboticsBrief- MERL's paper titled: "Closed-Loop Tactile Controller for Tool Manipulation" Won the Best Poster Award in the workshop on "Embracing contacts : Making robots physically interact with our world". First author and MERL intern, Yuki Shirai, was presented with the award at a ceremony held at ICRA in London. MERL researchers Devesh Jha, Principal Research Scientist, and Arvind Raghunathan, Senior Principal Research Scientist and Senior Team Leader as well as Prof. Dennis Hong of University of California, Los Angeles are also coauthors.
The paper presents a technique to manipulate an object using a tool in a closed-loop fashion using vision-based tactile sensors. More information about the workshop and the various speakers can be found here https://sites.google.com/view/icra2023embracingcontacts/home.
- MERL's paper titled: "Closed-Loop Tactile Controller for Tool Manipulation" Won the Best Poster Award in the workshop on "Embracing contacts : Making robots physically interact with our world". First author and MERL intern, Yuki Shirai, was presented with the award at a ceremony held at ICRA in London. MERL researchers Devesh Jha, Principal Research Scientist, and Arvind Raghunathan, Senior Principal Research Scientist and Senior Team Leader as well as Prof. Dennis Hong of University of California, Los Angeles are also coauthors.
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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, OptimizationBrief- 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.
- 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).
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AWARD Outstanding Presentation Award at the 28th Conference of Information Processing Society of Japan/Consumer Device & Systems Date: October 20, 2020
Awarded to: Yukimasa Nagai, Takenori Sumi, Jianlin Guo, Philip Orlik, Hiroshi Mineno
MERL Contacts: Jianlin Guo; Philip V. Orlik
Research Areas: Communications, Optimization, Signal ProcessingBrief- MELCO and MERL researchers have won "Outstanding Presentation Award" at 28th Conference of Information Processing Society of Japan (IPSJ)/Consumer Device & Systems held on September 29-30, 2020. The paper titled "IEEE 802.19.3 Standardization for Coexistence of IEEE 802.11ah and IEEE 802.15.4g Systems in Sub-1 GHz Frequency Bands" reports IEEE 802.19.3 standard development on coexistence between IEEE 802.11ah and IEEE 802.15.4g systems in the Sub-1 GHz frequency bands. MERL and MELCO have been leading this standard development and made major technical contributions, which propose methods to mitigate interference in smart meter systems. The authors are Yukimasa Nagai, Takenori Sumi, Jianlin Guo, Philip Orlik and Hiroshi Mineno.
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News & Events
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NEWS Toshiaki Koike-Akino to give a tutorial talk at ISIT 2025 Quantum Hackathon Date: June 22, 2025
Where: IEEE International Symposium on Information Theory (ISIT)
MERL Contact: Toshiaki Koike-Akino
Research Areas: Artificial Intelligence, Communications, Data Analytics, Machine Learning, Optimization, Signal Processing, Human-Computer Interaction, Information SecurityBrief- Toshiaki Koike-Akino is invited to present a tutorial talk at IEEE ISIT 2025 Quantum Hackathon, to be held at Ann Arbor, Michigan, USA. The talk, entitled "Emerging Quantum AI Technology", will discuss the recent trends, challenges, and applications of quantum artificial intelligence (QAI) technologies.
The ISIT 2025 Quantum Hackathon invites participants to explore the intersection of quantum computing and information theory. Participants will work with quantum simulators, available quantum hardware, and state-of-the-art development kits to create innovative solutions that connect quantum advancements with challenges in communication and signal processing.
The IEEE International Symposium on Information Theory (ISIT) is the flagship conference of the IEEE Information Theory Society. The symposium centers around the presentation in all of the areas of information theory, including source and channel coding, communication theory and systems, cryptography and security, detection and estimation, networks, pattern recognition and learning, statistics, stochastic processes and complexity, and signal processing.
- Toshiaki Koike-Akino is invited to present a tutorial talk at IEEE ISIT 2025 Quantum Hackathon, to be held at Ann Arbor, Michigan, USA. The talk, entitled "Emerging Quantum AI Technology", will discuss the recent trends, challenges, and applications of quantum artificial intelligence (QAI) technologies.
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NEWS MERL contributes to ICRA 2025 Date: May 19, 2025 - May 23, 2025
Where: IEEE ICRA
MERL Contacts: Stefano Di Cairano; Jianlin Guo; Chiori Hori; Siddarth Jain; Devesh K. Jha; Toshiaki Koike-Akino; Philip V. Orlik; Arvind Raghunathan; Diego Romeres; Yuki Shirai; Abraham P. Vinod; Yebin Wang
Research Areas: Artificial Intelligence, Computer Vision, Control, Dynamical Systems, Machine Learning, Optimization, Robotics, Human-Computer InteractionBrief- MERL made significant contributions to both the organization and the technical program of the International Conference on Robotics and Automation (ICRA) 2025, which was held in Atlanta, Georgia, USA, from May 19th to May 23rd.
MERL was a Bronze sponsor of the conference, and MERL researchers chaired four sessions in the areas of Manipulation Planning, Human-Robot Collaboration, Diffusion Policy, and Learning for Robot Control.
MERL researchers presented four papers in the main conference on the topics of contact-implicit trajectory optimization, proactive robotic assistance in human-robot collaboration, diffusion policy with human preferences, and dynamic and model learning of robotic manipulators. In addition, five more papers were presented in the workshops: “Structured Learning for Efficient, Reliable, and Transparent Robots,” “Safely Leveraging Vision-Language Foundation Models in Robotics: Challenges and Opportunities,” “Long-term Human Motion Prediction,” and “The Future of Intelligent Manufacturing: From Innovation to Implementation.”
MERL researcher Diego Romeres delivered an invited talk titled “Dexterous Robotics: From Multimodal Sensing to Real-World Physical Interactions.”
MERL also collaborated with the University of Padua on one of the conference’s challenges: the “3rd AI Olympics with RealAIGym” (https://ai-olympics.dfki-bremen.de).
During the conference, MERL researchers received the IEEE Transactions on Automation Science and Engineering Best New Application Paper Award for their paper titled “Smart Actuation for End-Edge Industrial Control Systems.”
About ICRA
The IEEE International Conference on Robotics and Automation (ICRA) is the flagship conference of the IEEE Robotics and Automation Society and the world’s largest and most comprehensive technical conference focused on research advances and the latest technological developments in robotics. The event attracts over 7,000 participants, 143 partners and exhibitors, and receives more than 4,000 paper submissions.
- MERL made significant contributions to both the organization and the technical program of the International Conference on Robotics and Automation (ICRA) 2025, which was held in Atlanta, Georgia, USA, from May 19th to May 23rd.
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Research Highlights
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Internships
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OR0115: Internship - Whole-body dexterous manipulation
MERL is looking for a highly motivated individual to work on whole-body dexterous manipulation. The research will develop robot motor skills for whole-body, dexterous manipulation using optimization and/or learning algorithms. The ideal candidate should have experience in either one or multiple of the following topics: Optimization Algorithms for contact systems, Reinforcement Learning, control through contacts, and Behavioral cloning. Senior PhD students in robotics and engineering with a focus on contact-rich manipulation are encouraged to apply. Prior experience working with physical robotic systems (and vision and tactile sensors) is required as results need to be implemented on a physical hardware. Good coding skills in Python ML libraries like PyTorch etc. and/or relevant Optimization packages is required. A successful internship will result in submission of results to a peer-reviewed robotics journal in collaboration with MERL researchers. The expected duration of internship is 4-5 months with start date in May/June 2025. This internship is preferred to be onsite at MERL.
Required Specific Experience
- Prior experience working with physical hardware system is required.
- Prior publication experience in robotics venues like ICRA,RSS, CoRL.
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MS0098: Internship - Control and Estimation for Large-Scale Thermofluid Systems
MERL is seeking a motivated graduate student to research methods for state and parameter estimation and optimization of large-scale systems for process applications. Representative applications include large vapor-compression cycles and other multiphysical systems for energy conversion that couple thermodynamic, fluid, and electrical domains. The ideal candidate would have a solid background in control and estimation, numerical methods, and optimization; strong programming skills and experience with Julia/Python/Matlab are also expected. Knowledge of the fundamental physics of thermofluid flows (e.g., thermodynamics, heat transfer, and fluid mechanics), nonlinear dynamics, or equation-oriented languages (Modelica, gPROMS) is a plus. The expected duration of this internship is 3 months.
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MS0156: Internship - Stochastic Model Predictive Control with Generative Models for Smart Building Control
MERL is looking for a research intern to develop efficient transformer-informed stochastic MPC to control net-zero energy buildings. This is an exciting opportunity to make a real impact in the field of cutting-edge deep learning and predictive control on a real system. Publication of results produced during the internship is desired. The expected duration of the internship is 3-6 months with a flexible start date.
The Ideal Candidate Will Have:
- Significant hands-on experience with stochastic MPC
- Publications in SMPC are a strong plus
- Fluency in Python and PyTorch
- Understanding of probabilistic time-series prediction
- Experience with convex programming
- Convex formulations of MPC/SMPC problems are a strong plus
- Completed their MS, or >50% of their PhD program
Mitsubishi Electric Research Labs, Inc. "MERL" provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, MERL complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
MERL expressly prohibits any form of workplace harassment based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. Improper interference with the ability of MERL’s employees to perform their job duties may result in discipline up to and including discharge.
Working at MERL requires full authorization to work in the U.S and access to technology, software and other information that is subject to governmental access control restrictions, due to export controls. Employment is conditioned on continued full authorization to work in the U.S and the availability of government authorization for the release of these items, which might include without limitation, obtaining an export license or other documentation. MERL may delay commencement of employment, rescind an offer of employment, terminate employment, and/or modify job responsibilities, compensation, benefits, and/or access to MERL facilities and information systems, as MERL deems appropriate, to ensure practical compliance with applicable employment law and government access control restrictions.
- Significant hands-on experience with stochastic MPC
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Openings
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EA0042: Research Scientist - Control & Learning
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OR0052: Research Scientist - Optimization Algorithms
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CA0093: Research Scientist - Control for Autonomous Systems
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CI0130: Postdoctoral Research Fellow - Artificial General Intelligence (AGI)
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Recent Publications
- "Topology Optimization of Electric Motors using Mesh Projection", International Conference on the Computation of Electromagnetic Fields (COMPUMAG), June 2025.BibTeX TR2025-089 PDF
- @inproceedings{Das2025jun2,
- author = {Das, Ghanendra and Wang, Bingnan and Lin, Chungwei},
- title = {{Topology Optimization of Electric Motors using Mesh Projection}},
- booktitle = {International Conference on the Computation of Electromagnetic Fields (COMPUMAG)},
- year = 2025,
- month = jun,
- url = {https://www.merl.com/publications/TR2025-089}
- }
, - "Physics-informed Machine Learning with Heuristic Feedback Control Layer for Autonomous Vehicle Control", IEEE Intelligent Vehicles Symposium (IV), June 2025.BibTeX TR2025-087 PDF
- @inproceedings{Li2025jun2,
- author = {Li, Xianning and Wang, Yebin and Ozbay, Kaan and Jiang, Zhong-Ping},
- title = {{Physics-informed Machine Learning with Heuristic Feedback Control Layer for Autonomous Vehicle Control}},
- booktitle = {IEEE Intelligent Vehicles Symposium (IV)},
- year = 2025,
- month = jun,
- url = {https://www.merl.com/publications/TR2025-087}
- }
, - "pycvxset: A Python package for convex set manipulation", American Control Conference (ACC), June 2025.BibTeX TR2025-086 PDF Software
- @inproceedings{Vinod2025jun,
- author = {Vinod, Abraham P.},
- title = {{pycvxset: A Python package for convex set manipulation}},
- booktitle = {American Control Conference (ACC)},
- year = 2025,
- month = jun,
- url = {https://www.merl.com/publications/TR2025-086}
- }
, - "FDPP: Fine-tune Diffusion Policy with Human Preference", IEEE International Conference on Robotics and Automation (ICRA), May 2025.BibTeX TR2025-053 PDF Video
- @inproceedings{Chen2025may,
- author = {Chen, Yuxin and Jha, Devesh K. and Tomizuka, Masayoshi and Romeres, Diego},
- title = {{FDPP: Fine-tune Diffusion Policy with Human Preference}},
- booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
- year = 2025,
- month = may,
- url = {https://www.merl.com/publications/TR2025-053}
- }
, - "Hierarchical Contact-Rich Trajectory Optimization for Multi-Modal Manipulation using Tight Convex Relaxations", IEEE International Conference on Robotics and Automation (ICRA), May 2025.BibTeX TR2025-052 PDF
- @inproceedings{Shirai2025may,
- author = {Shirai, Yuki and Raghunathan, Arvind and Jha, Devesh K.},
- title = {{Hierarchical Contact-Rich Trajectory Optimization for Multi-Modal Manipulation using Tight Convex Relaxations}},
- booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
- year = 2025,
- month = may,
- url = {https://www.merl.com/publications/TR2025-052}
- }
, - "Simultaneous Trajectory Optimization and Contact Selection for Contact-rich Manipulation with High-Fidelity Geometry", IEEE Transactions on Robotics (T-RO), April 2025.BibTeX TR2025-047 PDF
- @article{Zhang2025apr,
- author = {Zhang, Mengchao and Jha, Devesh K. and Raghunathan, Arvind and Hauser, Kris},
- title = {{Simultaneous Trajectory Optimization and Contact Selection for Contact-rich Manipulation with High-Fidelity Geometry}},
- journal = {IEEE Transactions on Robotics (T-RO)},
- year = 2025,
- month = apr,
- url = {https://www.merl.com/publications/TR2025-047}
- }
, - "Time-Series Generative Networks for Synthesizing Realistic Scenarios in Occupant-Centric Building Simulation", Building Simulation, April 2025.BibTeX TR2025-043 PDF
- @article{Chakrabarty2025apr,
- author = {Chakrabarty, Ankush and Vanfretti, Luigi and Wang, Ye and Mineyuki, Takuma and Zhan, Sicheng and Tang, Wei-Ting and Paulson, Joel A. and Deshpande, Vedang M. and Bortoff, Scott A. and Laughman, Christopher R.},
- title = {{Time-Series Generative Networks for Synthesizing Realistic Scenarios in Occupant-Centric Building Simulation}},
- journal = {Building Simulation},
- year = 2025,
- month = apr,
- url = {https://www.merl.com/publications/TR2025-043}
- }
, - "Projection-free computation of robust controllable sets with constrained zonotopes", Automatica, DOI: 10.1016/j.automatica.2025.112211, Vol. 175, pp. 112211, March 2025.BibTeX TR2025-023 PDF Video
- @article{Vinod2025mar,
- author = {Vinod, Abraham P. and Weiss, Avishai and Di Cairano, Stefano},
- title = {{Projection-free computation of robust controllable sets with constrained zonotopes}},
- journal = {Automatica},
- year = 2025,
- volume = 175,
- pages = 112211,
- month = mar,
- doi = {10.1016/j.automatica.2025.112211},
- issn = {0005-1098},
- url = {https://www.merl.com/publications/TR2025-023}
- }
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- "Topology Optimization of Electric Motors using Mesh Projection", International Conference on the Computation of Electromagnetic Fields (COMPUMAG), June 2025.
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Videos
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Software & Data Downloads
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Optimal Recursive McCormick Linearization of MultiLinear Programs -
Convex sets in Python -
Meta-Learning State Space Models -
Python-based Robotic Control & Optimization Package -
Template Embeddings for Adiabatic Quantum Computation -
Quasi-Newton Trust Region Policy Optimization -
Convergent Inverse Scattering using Optimization and Regularization
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