Multi-Physical Modeling
Optimal design & robust control through multi-physical modeling.
Our work involves the development of state-of-art modeling and simulation tools for complex, heterogeneous systems. We apply these models for the optimal design and robust control of a variety of systems including HVAC systems, zero-energy buildings, automobiles, and robotic systems.
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Researchers
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Awards
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AWARD Mitsubishi Electric Team Wins Awards at GalFer Contest Date: June 23, 2025
Awarded to: Bingnan Wang, Tatsuya Yamamoto, Yusuke Sakamoto, Siyuan Sun, Toshiaki Koike-Akino, and Ye Wang
MERL Contacts: Toshiaki Koike-Akino; Bingnan Wang; Ye Wang
Research Areas: Machine Learning, Multi-Physical Modeling, OptimizationBrief- The MELSUR (Mitsubishi Electric SURrogate) team, consisting of a group of MERL and Mitsubishi Electric researchers, ranked first in two out of three categories in the GalFer Contest.
The GalFer (Galileo Ferraris) contest aims to compare the accuracy and efficiency of data-driven methodologies for the multi-physics simulation of traction electric machines. A total of 26 teams worldwide participated in the contest, which consists of three categories. The MELSUR team, including MERL staff Bingnan Wang, Toshiaki Koike-Akino, Ye Wang, MERL intern Siyuan Sun, Mitsubishi Electric researchers Tatsuya Yamamoto and Yusuke Sakamoto, ranked first for the category of "Novelty" and "Interpolation". The results were announced during an award ceremony at the COMPUMAG 2025 conference in Naples, Italy.
- The MELSUR (Mitsubishi Electric SURrogate) team, consisting of a group of MERL and Mitsubishi Electric researchers, ranked first in two out of three categories in the GalFer Contest.
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AWARD Best Paper Award at SDEMPED 2023 Date: August 30, 2023
Awarded to: Bingnan Wang, Hiroshi Inoue, and Makoto Kanemaru
MERL Contact: Bingnan Wang
Research Areas: Applied Physics, Data Analytics, Multi-Physical ModelingBrief- MERL and Mitsubishi Electric's paper titled “Motor Eccentricity Fault Detection: Physics-Based and Data-Driven Approaches” was awarded one of three best paper awards at the 14th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED 2023). MERL Senior Principal Research Scientist Bingnan Wang presented the paper and received the award at the symposium. Co-authors of the paper include Mitsubishi Electric researchers Hiroshi Inoue and Makoto Kanemaru.
SDEMPED was established as the only international symposium entirely devoted to the diagnostics of electrical machines, power electronics and drives. It is now a regular biennial event. The 14th version, SDEMPED 2023 was held in Chania, Greece from August 28th to 31st, 2023.
- MERL and Mitsubishi Electric's paper titled “Motor Eccentricity Fault Detection: Physics-Based and Data-Driven Approaches” was awarded one of three best paper awards at the 14th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED 2023). MERL Senior Principal Research Scientist Bingnan Wang presented the paper and received the award at the symposium. Co-authors of the paper include Mitsubishi Electric researchers Hiroshi Inoue and Makoto Kanemaru.
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News & Events
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NEWS MERL Researchers at NeurIPS 2025 presented 2 conference papers, 5 workshop papers, and organized a workshop. Date: December 2, 2025 - December 7, 2025
Where: San Diego
MERL Contacts: Petros T. Boufounos; Anoop Cherian; Radu Corcodel; Stefano Di Cairano; Chiori Hori; Christopher R. Laughman; Suhas Anand Lohit; Pedro Miraldo; Saviz Mowlavi; Kuan-Chuan Peng; Arvind Raghunathan; Diego Romeres; Abraham P. Vinod; Pu (Perry) Wang
Research Areas: Artificial Intelligence, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & AudioBrief- MERL researchers presented 2 main-conference papers and 5 workshop papers, as well as organized a workshop, at NeurIPS 2025.
Main Conference Papers:
1) Sorachi Kato, Ryoma Yataka, Pu Wang, Pedro Miraldo, Takuya Fujihashi, and Petros Boufounos, "RAPTR: Radar-based 3D Pose Estimation using Transformer", Code available at: https://github.com/merlresearch/radar-pose-transformer
2) Runyu Zhang, Arvind Raghunathan, Jeff Shamma, and Na Li, "Constrained Optimization From a Control Perspective via Feedback Linearization"
Workshop Papers:
1) Yuyou Zhang, Radu Corcodel, Chiori Hori, Anoop Cherian, and Ding Zhao, "SpinBench: Perspective and Rotation as a Lens on Spatial Reasoning in VLMs", NeuriIPS 2025 Workshop on SPACE in Vision, Language, and Embodied AI (SpaVLE) (Best Paper Runner-up)
2) Xiaoyu Xie, Saviz Mowlavi, and Mouhacine Benosman, "Smooth and Sparse Latent Dynamics in Operator Learning with Jerk Regularization", Workshop on Machine Learning and the Physical Sciences (ML4PS)
3) Spencer Hutchinson, Abraham Vinod, François Germain, Stefano Di Cairano, Christopher Laughman, and Ankush Chakrabarty, "Quantile-SMPC for Grid-Interactive Buildings with Multivariate Temporal Fusion Transformers", Workshop on UrbanAI: Harnessing Artificial Intelligence for Smart Cities (UrbanAI)
4) Yuki Shirai, Kei Ota, Devesh Jha, and Diego Romeres, "Sim-to-Real Contact-Rich Pivoting via Optimization-Guided RL with Vision and Touch", Worskhop on Embodied World Models for Decision Making
5) Mark Van der Merwe and Devesh Jha, "In-Context Policy Iteration for Dynamic Manipulation", Workshop on Embodied World Models for Decision Making
Workshop Organized:
MERL members co-organized the Multimodal Algorithmic Reasoning (MAR) Workshop (https://marworkshop.github.io/neurips25/). Organizers: Anoop Cherian (Mitsubishi Electric Research Laboratories), Kuan-Chuan Peng (Mitsubishi Electric Research Laboratories), Suhas Lohit (Mitsubishi Electric Research Laboratories), Honglu Zhou (Salesforce AI Research), Kevin Smith (Massachusetts Institute of Technology), and Joshua B. Tenenbaum (Massachusetts Institute of Technology).
- MERL researchers presented 2 main-conference papers and 5 workshop papers, as well as organized a workshop, at NeurIPS 2025.
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NEWS MERL researchers present 13 papers at ACC 2025 Date: July 8, 2025 - July 10, 2025
Where: Denver, USA
MERL Contacts: Vedang M. Deshpande; Stefano Di Cairano; Purnanand Elango; Jordan Leung; Saviz Mowlavi; Diego Romeres; Abraham P. Vinod; Yebin Wang; Avishai Weiss
Research Areas: Control, Dynamical Systems, Electric Systems, Machine Learning, Multi-Physical Modeling, RoboticsBrief- MERL researchers presented 13 papers at the recently concluded American Control Conference (ACC) 2025 in Denver, USA. The papers covered a wide range of topics including Bayesian optimization for personalized medicine, machine learning for battery performance in eVTOLs, model predictive control for space and building systems, process systems engineering for sustainability, GNSS-RTK optimization, convex set manipulation, PDE control, servo system modeling, battery fault diagnosis, truck fleet coordination, interactive motion planning, and satellite station keeping. Additionally, MERL researchers (Vedang Deshpande and Ankush Chakrabarty) organized an invited session on design and optimization of energy systems.
As a sponsor of the conference, MERL maintained a booth for open discussions with researchers and students, and hosted a special session to discuss highlights of MERL research and work philosophy.
- MERL researchers presented 13 papers at the recently concluded American Control Conference (ACC) 2025 in Denver, USA. The papers covered a wide range of topics including Bayesian optimization for personalized medicine, machine learning for battery performance in eVTOLs, model predictive control for space and building systems, process systems engineering for sustainability, GNSS-RTK optimization, convex set manipulation, PDE control, servo system modeling, battery fault diagnosis, truck fleet coordination, interactive motion planning, and satellite station keeping. Additionally, MERL researchers (Vedang Deshpande and Ankush Chakrabarty) organized an invited session on design and optimization of energy systems.
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Internships
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MS0260: Internship - Experimental Thermofluid Systems
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EA0236: Internship - Topology Optimization
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ST0245: Internship - Python-OpenFOAM Interface for Active Flow Control
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Openings
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Recent Publications
- , "Quantile-SMPC for Grid-Interactive Buildings with Multivariate Temporal Fusion Transformers", Advances in Neural Information Processing Systems (NeurIPS) Workshop on UrbanAI, December 2025.BibTeX TR2026-001 PDF
- @inproceedings{Hutchinson2025dec,
- author = {{{Hutchinson, Spencer and Vinod, Abraham P. and Germain, François G and Di Cairano, Stefano and Laughman, Christopher R. and Chakrabarty, Ankush}}},
- title = {{{Quantile-SMPC for Grid-Interactive Buildings with Multivariate Temporal Fusion Transformers}}},
- booktitle = {Advances in Neural Information Processing Systems (NeurIPS) Workshop on UrbanAI},
- year = 2025,
- month = dec,
- url = {https://www.merl.com/publications/TR2026-001}
- }
- , "Electric Motor Topology Optimization via Rotated Filter Projection and Adjoint Sensitivities", IEEE Transactions on Magnetics, December 2025.BibTeX TR2025-164 PDF
- @article{Das2025dec,
- author = {Das, Ghanendra and Wang, Bingnan and Lin, Chungwei},
- title = {{Electric Motor Topology Optimization via Rotated Filter Projection and Adjoint Sensitivities}},
- journal = {IEEE Transactions on Magnetics},
- year = 2025,
- month = dec,
- url = {https://www.merl.com/publications/TR2025-164}
- }
- , "Meta-Learning for Physically-Constrained Neural System Identification", Neurocomputing, DOI: 10.1016/j.neucom.2025.130945, Vol. 651, pp. 130945, October 2025.BibTeX TR2025-159 PDF
- @article{Chakrabarty2025nov,
- author = {Chakrabarty, Ankush and Wichern, Gordon and Deshpande, Vedang M. and Vinod, Abraham P. and Berntorp, Karl and Laughman, Christopher R.},
- title = {{Meta-Learning for Physically-Constrained Neural System Identification}},
- journal = {Neurocomputing},
- year = 2025,
- volume = 651,
- pages = 130945,
- month = nov,
- doi = {10.1016/j.neucom.2025.130945},
- issn = {0925-2312},
- url = {https://www.merl.com/publications/TR2025-159}
- }
- , "QKAN-GS: Quantum-Empowered 3D Gaussian Splatting", ACM Multimedia Workshop, October 2025.BibTeX TR2025-156 PDF
- @inproceedings{Fujihashi2025oct,
- author = {Fujihashi, Takuya and Kuwabara, Akihiro and Koike-Akino, Toshiaki},
- title = {{QKAN-GS: Quantum-Empowered 3D Gaussian Splatting}},
- booktitle = {ACM Multimedia Workshop},
- year = 2025,
- month = oct,
- url = {https://www.merl.com/publications/TR2025-156}
- }
- , "A physics-constrained deep learning framework for dynamic modeling of vapor compression systems", Applied Energy, September 2025.BibTeX TR2025-137 PDF
- @article{Ma2025sep,
- author = {Ma, JiaCheng and Dong, Yiyun and Qiao, Hongtao and Laughman, Christopher R.},
- title = {{A physics-constrained deep learning framework for dynamic modeling of vapor compression systems}},
- journal = {Applied Energy},
- year = 2025,
- month = sep,
- url = {https://www.merl.com/publications/TR2025-137}
- }
- , "LSTM-Based Modeling and Cross-Correlation Sensitivity Analysis for Heat Pump Refrigerant Distribution", International Journal of Refrigeration, September 2025.BibTeX TR2025-141 PDF
- @article{Miyawaki2025sep,
- author = {Miyawaki, Kosuke and Qiao, Hongtao and Sciazko, Anna and Shikazono, Naoki},
- title = {{LSTM-Based Modeling and Cross-Correlation Sensitivity Analysis for Heat Pump Refrigerant Distribution}},
- journal = {International Journal of Refrigeration},
- year = 2025,
- month = sep,
- url = {https://www.merl.com/publications/TR2025-141}
- }
- , "A Dynamic Analysis of Refrigerant Mass in Vapor Compression Cycles", International Modelica Conference, September 2025.BibTeX TR2025-135 PDF
- @inproceedings{Bortoff2025sep,
- author = {Bortoff, Scott A. and Deshpande, Vedang M. and Laughman, Christopher R. and Qiao, Hongtao},
- title = {{A Dynamic Analysis of Refrigerant Mass in Vapor Compression Cycles}},
- booktitle = {International Modelica Conference},
- year = 2025,
- month = sep,
- url = {https://www.merl.com/publications/TR2025-135}
- }
- , "Zero-Shot Parameter Estimation of Modelica Models using Patch Transformer Networks", International Modelica and FMI Conference, September 2025.BibTeX TR2025-133 PDF
- @inproceedings{Chakrabarty2025sep,
- author = {Chakrabarty, Ankush and Forgione, Marco and Piga, Dario and Bemporad, Alberto and Laughman, Christopher R.},
- title = {{Zero-Shot Parameter Estimation of Modelica Models using Patch Transformer Networks}},
- booktitle = {International Modelica and FMI Conference},
- year = 2025,
- month = sep,
- url = {https://www.merl.com/publications/TR2025-133}
- }
- , "Quantile-SMPC for Grid-Interactive Buildings with Multivariate Temporal Fusion Transformers", Advances in Neural Information Processing Systems (NeurIPS) Workshop on UrbanAI, December 2025.
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