Siddarth Jain

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sjain {at} merl[dot]com

Siddarth is a Principal Research Scientist at Mitsubishi Electric Research Laboratories (MERL). His research spans computer vision, machine learning, and robotics, with a focus on enabling autonomous systems to perceive, understand, and act in the physical world. He develops data-driven and geometric approaches for learning, perception, manipulation, and decision-making, with applications in human–robot collaboration and real-world automation. He also serves as an Associate Editor for IEEE Robotics and Automation Letters (RA-L).

He received his Ph.D. in Computer Science from Northwestern University in 2019. In collaboration with the Shirley Ryan AbilityLab, his research focused on probabilistic human intent recognition and adaptive assistance in shared-autonomy for robot teleoperation, involving interactive assistive systems and user studies. He also developed perception algorithms to infer goals for navigation and robotic manipulation.

news

Jan 31, 2026 2 papers have been accepted for publication at ICRA 2026, Vienna, Austria.
Nov 19, 2025 We are hiring a Ph.D. student for Robot Learning / Perception internship. Please apply here.
May 19, 2025 Presenting 2 papers at ICRA 2025.
May 19, 2025 Serving as a session chair for Human-Robot Collaboration at ICRA 2025.
Oct 14, 2024 Presenting 5 papers at IROS 2024.
May 13, 2024 Presenting a live demo on Autonomous Assembly at ICRA 2024, Yokohama, Japan.
Jan 09, 2024 Presenting a live demo at CES 2024, Las Vegas, USA.

selected publications

  1. earl.gif
    EARL: Eye-on-hand Reinforcement Learner for Dynamic Grasping with Active Pose Estimation
    Baichuan Huang, Jingjin Yu, and Siddarth Jain
    In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023
    : Dynamic Grasping | Reinforcement Learning | Pose Estimation | Closed-Loop Control | Visual Servoing
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    Insert-One: One-shot Robust Visual-Force Servoing for Novel Object Insertion with 6-DoF Tracking
    Haonan Chang, Abdeslam Boularias, and Siddarth Jain
    In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024
    : Assembly | Robotic Insertion | Visual-Force Servoing | Robust Manipulation | Visual Tracking
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    Probabilistic Human Intent Recognition for Shared Autonomy in Assistive Robotics
    Siddarth Jain and Brenna Argall
    ACM Transactions on Human-Robot Interaction (THRI), 2019
    : Shared Autonomy | Human Intent Recognition | Bayesian Inference | Assistive Robotics | HRI
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    Open Human-Robot Collaboration using Decentralized Inverse Reinforcement Learning
    Prasanth Sengadu Suresh, Siddarth Jain, Prashant Doshi, and Diego Romeres
    In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024
    : Inverse Reinforcement Learning | Multi-Agent Systems | Collaborative Assembly | HRI
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    Assistive Robotic Manipulation through Shared Autonomy and a Body-Machine Interface
    Siddarth Jain, Ali Farshchiansadegh, Alexander Broad, Farnaz Abdollahi, Ferdinando Mussa-Ivaldi, and Brenna Argall
    In Proceedings of the IEEE International Conference on Rehabilitation Robotics (ICORR), 2015
    : Body-Machine Interface | Shared Control | Assistive Robotics
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    Discriminative 3D Shape Modeling for Few-Shot Instance Segmentation
    Anoop Cherian, Siddarth Jain, Tim K Marks, and Alan Sullivan
    In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2023
    : Instance Segmentation | Shape Modeling | Few-Shot Learning | Computer Vision
  7. grasp.png
    Grasp Detection for Assistive Robotic Manipulation
    Siddarth Jain and Brenna Argall
    In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2016
    : Grasping | Shape Primitives | Point Clouds | Grasp Detection
  8. docking.gif
    Automated Perception of Safe Docking Locations with Alignment Information for Assistive Wheelchairs
    Siddarth Jain and Brenna Argall
    In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2014
    : Docking Detection | Point Clouds | Computer Vision | Assistive Robotics