Machine Learning

Data-driven approaches to design intelligent algorithms.

MERL has a long history of research activity in machine learning, including the development of various boosting algorithms and contributing to the theory and practice of highly scalable collaborative filtering. Our recent work has focused on deep learning and reinforcement learning, with application to a wide range of applications including automotive, robotics, factory automation, transportation, as well as building and home systems.

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Researchers
Awards
- 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, Optimization
  Brief
  - 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.
- AWARD MERL work receives IEEE Transactions on Automation Science and Engineering Best New Application Paper Award from IEEE Robotics and Automation Society
  Date: May 19, 2025
  Awarded to: Yehan Ma, Yebin Wang, Stefano Di Cairano, Toshiaki Koike-Akino, Jianlin Guo, Philip Orlik, Xinping Guan and Chenyang Lu
  MERL Contacts: Stefano Di Cairano; Jianlin Guo; Toshiaki Koike-Akino; Philip V. Orlik; Yebin Wang
  Research Areas: Communications, Control, Machine Learning
  Brief
  - The paper “Smart Actuation for End-Edge Industrial Control Systems”, co-authored by MERL intern Yehan Ma, MERL researchers Yebin Wang, Stefano Di Cairano, Toshiaki Koike-Akino, Jianlin Guo, and Philip Orlik, and academic collaborators Xinping Guan and Chenyang Lu, was recognized as the Best New Application Paper of the IEEE Transactions on Automation Science and Engineering (T-ASE), for "a new industrial automation solution that ensures safety operation through coordinated co-design of edge model predictive control and local actuation".
    
    The award recognizes the best application paper published in T-ASE over the previous calendar year, for the significance of new applications, technical merit, originality, potential impact on the field, and clarity of presentation.
- AWARD MERL Wins Awards at NeurIPS LLM Privacy Challenge
  Date: December 15, 2024
  Awarded to: Jing Liu, Ye Wang, Toshiaki Koike-Akino, Tsunato Nakai, Kento Oonishi, Takuya Higashi
  MERL Contacts: Toshiaki Koike-Akino; Jing Liu; Ye Wang
  Research Areas: Artificial Intelligence, Machine Learning, Information Security
  Brief
  - The Mitsubishi Electric Privacy Enhancing Technologies (MEL-PETs) team, consisting of a collaboration of MERL and Mitsubishi Electric researchers, won awards at the NeurIPS 2024 Large Language Model (LLM) Privacy Challenge. In the Blue Team track of the challenge, we won the 3rd Place Award, and in the Red Team track, we won the Special Award for Practical Attack.
See All Awards for Machine Learning
News & Events
- NEWS MERL Papers, Workshops, and Talks at ICCV 2025
  Date: October 19, 2025 - October 23, 2025
  Where: Honolulu, HI, USA
  MERL Contacts: Petros T. Boufounos; Anoop Cherian; Toshiaki Koike-Akino; Hassan Mansour; Tim K. Marks; Pedro Miraldo; Kuan-Chuan Peng; Pu (Perry) Wang
  Research Areas: Artificial Intelligence, Computer Vision, Machine Learning, Signal Processing
  Brief
  - MERL researchers presented 3 conference papers and 3 workshop papers, co-organized 2 workshops, and delivered 2 invited talks at the IEEE International Conference on Computer Vision (ICCV) 2025, which was held in Honolulu, HI, USA from October 19-23, 2025. ICCV is one of the most prestigious and competitive international conferences in the area of computer vision. Details of MERL contributions are provided below:
    
    Main Conference Papers:
    
    1. "SAC-GNC: SAmple Consensus for adaptive Graduated Non-Convexity" by V. Piedade, C. Sidhartha, J. Gaspar, V. M. Govindu, and P. Miraldo. (Highlight Paper)
    Paper: https://www.merl.com/publications/TR2025-146
    
    2. "Toward Long-Tailed Online Anomaly Detection through Class-Agnostic Concepts" by C.-A. Yang, K.-C. Peng, and R. A. Yeh.
    Paper: https://www.merl.com/publications/TR2025-124
    
    3. "Manual-PA: Learning 3D Part Assembly from Instruction Diagrams" by J. Zhang, A. Cherian, C. Rodriguez-Opazo, W. Deng, and S. Gould.
    Paper: https://www.merl.com/publications/TR2025-139
    
    MERL Co-Organized Workshops:
    
    1. "The Workshop on Anomaly Detection with Foundation Models (ADFM)" by K.-C. Peng, Y. Zhao, and A. Aich.
    Workshop link: https://adfmw.github.io/iccv25/
    
    2. "The 8th International Workshop on Computer Vision for Physiological Measurement (CVPM)" by D. McDuff, W. Wang, S. Stuijk, T. Marks, H. Mansour, V. R. Shenoy.
    Workshop link: https://sstuijk.estue.nl/cvpm/cvpm25/
    
    MERL Keynote Talks at Workshops:
    
    1. Tim K. Marks, Keynote Speaker at the Workshop on Computer Vision for Physiological Measurement (CVPM).
    Workshop website: https://vineetrshenoy.github.io/cvpmSeptember2025/
    
    2. Tim K. Marks, Keynote Speaker at the Workshop on Analysis and Modeling of Faces and Gestures (AMFG).
    Workshop website: https://fulab.sites.northeastern.edu/amfg2025/
    
    Workshop Papers:
    
    1. "Joint Training of Image Generator and Detector for Road Defect Detection" by K.-C. Peng.
    paper: https://www.merl.com/publications/TR2025-149
    
    2. "Radar-Conditioned 3D Bounding Box Diffusion for Indoor Human Perception" by R. Yataka, P. Wang, P.T. Boufounos, and R. Takahashi.
    paper: https://www.merl.com/publications/TR2025-154
    
    3. "L-GGSC: Learnable Graph-based Gaussian Splatting Compression" by S. Kato, T. Koike-Akino, and T. Fujihashi.
    paper: https://www.merl.com/publications/TR2025-148
- NEWS MERL Papers, Workshops, and Talks at ICCV 2025
  Date: October 19, 2025 - October 23, 2025
  Where: Honolulu, HI, USA
  MERL Contacts: Petros T. Boufounos; Anoop Cherian; Toshiaki Koike-Akino; Hassan Mansour; Tim K. Marks; Pedro Miraldo; Kuan-Chuan Peng; Pu (Perry) Wang
  Research Areas: Artificial Intelligence, Computer Vision, Machine Learning, Signal Processing
  Brief
  - MERL researchers presented 3 conference papers and 3 workshop papers, co-organized 2 workshops, and delivered 2 invited talks at the IEEE International Conference on Computer Vision (ICCV) 2025, which was held in Honolulu, HI, USA from October 19-23, 2025. ICCV is one of the most prestigious and competitive international conferences in the area of computer vision. Details of MERL contributions are provided below:
    
    Main Conference Papers:
    
    1. "SAC-GNC: SAmple Consensus for adaptive Graduated Non-Convexity" by V. Piedade, C. Sidhartha, J. Gaspar, V. M. Govindu, and P. Miraldo. (Highlight Paper)
    Paper: https://www.merl.com/publications/TR2025-146
    
    2. "Toward Long-Tailed Online Anomaly Detection through Class-Agnostic Concepts" by C.-A. Yang, K.-C. Peng, and R. A. Yeh.
    Paper: https://www.merl.com/publications/TR2025-124
    
    3. "Manual-PA: Learning 3D Part Assembly from Instruction Diagrams" by J. Zhang, A. Cherian, C. Rodriguez-Opazo, W. Deng, and S. Gould.
    Paper: https://www.merl.com/publications/TR2025-139
    
    MERL Co-Organized Workshops:
    
    1. "The Workshop on Anomaly Detection with Foundation Models (ADFM)" by K.-C. Peng, Y. Zhao, and A. Aich.
    Workshop link: https://adfmw.github.io/iccv25/
    
    2. "The 8th International Workshop on Computer Vision for Physiological Measurement (CVPM)" by D. McDuff, W. Wang, S. Stuijk, T. Marks, H. Mansour, V. R. Shenoy.
    Workshop link: https://sstuijk.estue.nl/cvpm/cvpm25/
    
    MERL Keynote Talks at Workshops:
    
    1. Tim K. Marks, Keynote Speaker at the Workshop on Computer Vision for Physiological Measurement (CVPM).
    Workshop website: https://vineetrshenoy.github.io/cvpmSeptember2025/
    
    2. Tim K. Marks, Keynote Speaker at the Workshop on Analysis and Modeling of Faces and Gestures (AMFG).
    Workshop website: https://fulab.sites.northeastern.edu/amfg2025/
    
    Workshop Papers:
    
    1. "Joint Training of Image Generator and Detector for Road Defect Detection" by K.-C. Peng.
    paper: https://www.merl.com/publications/TR2025-149
    
    2. "Radar-Conditioned 3D Bounding Box Diffusion for Indoor Human Perception" by R. Yataka, P. Wang, P.T. Boufounos, and R. Takahashi.
    paper: https://www.merl.com/publications/TR2025-154
    
    3. "L-GGSC: Learnable Graph-based Gaussian Splatting Compression" by S. Kato, T. Koike-Akino, and T. Fujihashi.
    paper: https://www.merl.com/publications/TR2025-148
See All News & Events for Machine Learning
Research Highlights
Internships
See All Internships for Machine Learning
Openings
- CI0177: Postdoctoral Research Fellow - Agentic AI
- CA0093: Research Scientist - Control for Autonomous Systems
See All Openings at MERL
Recent Publications
- Sun, H., Otake, Y., Matsuyama, K., Raghunathan, A., "Switchgear Partial Discharge Diagnosis Using Scarce Fault Records", IEEE PES Innovative Smart Grid Technologies Conference - Europe (ISGT Europe), October 2025.
  BibTeX TR2025-155 PDF
  - @inproceedings{Sun2025oct,
  - author = {Sun, Hongbo and Otake, Yasutomo and Matsuyama, Kotaro and Raghunathan, Arvind},
  - title = {{Switchgear Partial Discharge Diagnosis Using Scarce Fault Records}},
  - booktitle = {IEEE PES Innovative Smart Grid Technologies Conference - Europe (ISGT Europe)},
  - year = 2025,
  - month = oct,
  - url = {https://www.merl.com/publications/TR2025-155}
  - }
- Yataka, R., Wang, P., Boufounos, P.T., Takahashi, R., "Radar-Conditioned 3D Bounding Box Diffusion for Indoor Human Perception", IEEE International Conference on Computer Vision (ICCV) Workshop, October 2025.
  BibTeX TR2025-154 PDF
  - @inproceedings{Yataka2025oct,
  - author = {Yataka, Ryoma and Wang, Pu and Boufounos, Petros T. and Takahashi, Ryuhei},
  - title = {{Radar-Conditioned 3D Bounding Box Diffusion for Indoor Human Perception}},
  - booktitle = {IEEE International Conference on Computer Vision (ICCV) Workshop},
  - year = 2025,
  - month = oct,
  - url = {https://www.merl.com/publications/TR2025-154}
  - }
- Kuwabara, A., Kirihara, H., Kato, S., Koike-Akino, T., Fujihashi, T., "L-GGSC: Learnable Graph-based Gaussian Splatting Compression", IEEE International Conference on Computer Vision Workshops (ICCV), October 2025.
  BibTeX TR2025-148 PDF
  - @inproceedings{Kuwabara2025oct,
  - author = {Kuwabara, Akihiro and Kirihara, Hinata and Kato, Sorachi and Koike-Akino, Toshiaki and Fujihashi, Takuya},
  - title = {{L-GGSC: Learnable Graph-based Gaussian Splatting Compression}},
  - booktitle = {IEEE International Conference on Computer Vision Workshops (ICCV)},
  - year = 2025,
  - month = oct,
  - url = {https://www.merl.com/publications/TR2025-148}
  - }
- Ma, H., Dai, B., Ren, Z., Wang, Y., Li, N., "Offline Imitation Learning upon Arbitrary Demonstrations by Pre-Training Dynamics Representations", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2025.
  BibTeX TR2025-147 PDF
  - @inproceedings{Ma2025oct,
  - author = {Ma, Haitong and Dai, Bo and Ren, Zhaolin and Wang, Yebin and Li, Na},
  - title = {{Offline Imitation Learning upon Arbitrary Demonstrations by Pre-Training Dynamics Representations}},
  - booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  - year = 2025,
  - month = oct,
  - url = {https://www.merl.com/publications/TR2025-147}
  - }
- Peng, K.-C., "Joint Training of Image Generator and Detector for Road Defect Detection", IEEE International Conference on Computer Vision (ICCV) Workshops, October 2025.
  BibTeX TR2025-149 PDF Video Presentation
  - @inproceedings{Peng2025oct,
  - author = {{{Peng, Kuan-Chuan}}},
  - title = {{{Joint Training of Image Generator and Detector for Road Defect Detection}}},
  - booktitle = {IEEE International Conference on Computer Vision (ICCV) Workshops},
  - year = 2025,
  - month = oct,
  - url = {https://www.merl.com/publications/TR2025-149}
  - }
- Piedade, V., Chitturi, S., Gaspar, J., Govindu, V., Miraldo, P., "SAC-GNC: SAmple Consensus for adaptive Graduated Non-Convexity", IEEE International Conference on Computer Vision (ICCV), October 2025.
  BibTeX TR2025-146 PDF Presentation
  - @inproceedings{Piedade2025oct,
  - author = {{{Piedade, Valter and Chitturi, Sidhartha and Gaspar, Jose and Govindu, Venu and Miraldo, Pedro}}},
  - title = {{{SAC-GNC: SAmple Consensus for adaptive Graduated Non-Convexity}}},
  - booktitle = {IEEE International Conference on Computer Vision (ICCV)},
  - year = 2025,
  - month = oct,
  - url = {https://www.merl.com/publications/TR2025-146}
  - }
- Yang, C.-A., Peng, K.-C., Yeh, R., "Toward Long-Tailed Online Anomaly Detection through Class-Agnostic Concepts", IEEE International Conference on Computer Vision (ICCV), October 2025.
  BibTeX TR2025-124 PDF Video Data Presentation
  - @inproceedings{Yang2025oct,
  - author = {{{Yang, Chiao-An and Peng, Kuan-Chuan and Yeh, Raymond}}},
  - title = {{{Toward Long-Tailed Online Anomaly Detection through Class-Agnostic Concepts}}},
  - booktitle = {IEEE International Conference on Computer Vision (ICCV)},
  - year = 2025,
  - month = oct,
  - url = {https://www.merl.com/publications/TR2025-124}
  - }
- Shenoy, V., Wu, S., Comas, A., Lohit, S., Mansour, H., Marks, T.K., "Time-Series U-Net with Recurrence for Noise-Robust Imaging Photoplethysmography", IEEE Access, October 2025.
  BibTeX TR2025-145 PDF
  - @article{Shenoy2025oct,
  - author = {Shenoy, Vineet and Wu, Shaoju and Comas, Armand and Lohit, Suhas and Mansour, Hassan and Marks, Tim K.},
  - title = {{Time-Series U-Net with Recurrence for Noise-Robust Imaging Photoplethysmography}},
  - journal = {IEEE Access},
  - year = 2025,
  - month = oct,
  - url = {https://www.merl.com/publications/TR2025-145}
  - }
See All Publications for Machine Learning
Videos

[ICCV 2025] SAC-GNC: SAmple Consensus for adaptive Graduated Non-Convexity

[BMVC 2025] Towards Open-Vocabulary Multimodal 3D Object Detection with Attributes

[ICCV Workshop 2025] Joint Training of Image Generator and Detector for Road Defect Detection

[ICCV 2025] Toward Long-Tailed Online Anomaly Detection through Class-Agnostic Concepts

[CVPR 2025] TailedCore: Few-Shot Sampling for Unsupervised Long-Tail Noisy Anomaly Detection

FDPP: Fine-tune Diffusion Policy with Human Preference

[MERL Seminar Series Spring 2025] Red Teaming AI Agents in-the-wild: Revealing Deployment Vulnerabilities

[MERL Seminar Series Spring 2025] The Emergence of Generalizability and Semantic Low-Dim Subspaces in Diffusion Models

[MERL Seminar Series Spring 2025] Amplifying human performance in combinatorial competitive programming

[WACV 2025] Towards Zero-shot 3D Anomaly Localization

Data-driven Spatial Classification using Multi-Arm Bandits for Monitoring with Robot Teams

[NeurIPS 2024] MEL-PETs Defense for the NeurIPS 2024 LLM Privacy Challenge Blue Team Track

[NeurIPS 2024] MEL-PETs Joint-Context Attack for the NeurIPS 2024 LLM Privacy Challenge Red Team Track

[NeurIPS 2024] Evaluating Large Vision-and-Language Models on Children's Mathematical Olympiads

[MERL Seminar Series Fall 2024] Audio for Object and Spatial Awareness

[IROS 2024] Few-shot Transparent Instance Segmentation for Bin Picking

[MERL Seminar Series Fall 2024] Tools from cognitive science to understand the behavior of large language models

[ECCV 2024] PS-NEUS: A Probability-guided Sampler for Neural Implicit Surface Rendering

[ECCV 2024] Equivariant Spatio-Temporal Self-Supervision for LiDAR Object Detection

[CVPR 2024] SIRA: Scalable Inter-frame Relation and Association for Radar Perception

Decentralized, Safe, Multi-agent Motion Planning for Drones Under Uncertainty via Filtered Reinforcement Learning

[MERL Seminar Series Spring 2024] Neural Certificates and LLMs in Large-Scale Autonomy Design

[MERL Seminar Series Spring 2024] Decoding Hidden Worlds: Unprecedented Sensing and Connectivity for Climate, Robotics, & Smart Environments

Gear-NeRF: Free-Viewpoint Rendering and Tracking with Motion-aware Spatio-Temporal Sampling

[MERL Seminar Series Spring 2024] Are Emergent Abilities of Large Language Models a Mirage?

MERL's Quantum AI Technology

[GLOBECOM 2022/VCC 2023 Tutorial] Post-Deep Learning Era: Emerging Quantum Machine Learning for Sensing and Communications (Session 2)

[GLOBECOM 2022/VCC 2023 Tutorial] Post-Deep Learning Era: Emerging Quantum Machine Learning for Sensing and Communications (Session I)

[MERL Seminar Series Fall 2023] Robust and Physics-informed machine learning for low light imaging

[MERL Seminar Series Fall 2023] Multiplicity in Machine Learning

Multi-level Reasoning for Robotic Assembly: From Sequence Inference to Contact Selection

[MERL Seminar Series Fall 2023] Visual Programming - A compositional approach to building General Purpose Vision Systems

[MERL Seminar Series Fall 2023] The Confluence of Vision, Language, and Robotics

[MERL Seminar Series Fall 2023] A Process Systems Engineering Perspective on Carbon Capture: Key Challenges and Opportunities

[TRO 2024] Safe Multiagent Motion Planning Under Uncertainty for Drones Using Filtered Reinforcement Learning

Are Deep Neural Networks SMARTer than Second Graders?

[CVPR 2023] EVAL: Explainable Video Anomaly Localization

[MERL Seminar Series Spring 2023] Learning and Dynamical Systems

[MERL Seminar Series Spring 2023] Investigating Multi-Agent Reinforcement Learning for Grid-Interactive Smart Communities using CityLearn

[MERL Seminar Series Spring 2023] Pitfalls and Opportunities in Interpretable Machine Learning

[MERL Seminar Series Spring 2023] Neural Implicit Flow

[MERL Seminar Series Spring 2023] Towards Complex Language in Partially Observed Environments

[MERL Seminar Series Spring 2022] Hybrid robotics and implicit learning

Toshiaki Koike-Akino Gives Seminar Talk at IEEE Boston Photonics

[MERL Seminar Series Spring 2022] RLMPC: An Ideal Combination of Formal Optimal Control and Reinforcement Learning?

[MERL Seminar Series Spring 2022] Self-Supervised Scene Representation Learning

[MERL Seminar Series Spring 2022] Learning Speech Representations with Multimodal Self-Supervision

[MERL Seminar Series Spring 2022] Extreme optics design as a large-scale optimization problem

HealthCam: A system for non-contact monitoring of vital signs

[MERL Seminar Series 2021] Harnessing machine learning to build better Earth system models for climate projection

[MERL Seminar Series 2021] Deep probabilistic regression

[MERL Seminar Series 2021] Learning to See by Moving: Self-supervising 3D scene representations for perception, control, and visual reasoning

Control of Mechanical Systems via Feedback Linearization Based on Black-Box Gaussian Process Models

Application of Deep Learning for Nanophotonic Device Design (Invited)

Towards Human-Level Learning of Complex Physical Puzzles

Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry

Scene-Aware Interaction Technology

Action Detection Using A Deep Recurrent Neural Network

MERL Research on Autonomous Vehicles

Semantic Scene Labeling

Obstacle Detection

Deep Hierarchical Parsing for Semantic Segmentation

Global Local Face Upsampling Network
Software & Data Downloads

Software & Data Downloads

MERL is making Machine Learning software and data available to the research community:

Subject- and Dataset-Aware Neural Field for HRTF Modeling (SuDaField)
Open Vocabulary Attribute Detection Dataset (OVAD)
Task-Aware Unified Source Separation (TUSS)
Local Density-Based Anomaly Score Normalization for Domain Generalization (anomaly-score-normalization)
Long-Tailed Online Anomaly Detection dataset (LTOAD)
Group Representation Networks (G-RepsNets)

See All Downloads