Siddarth Jain

Siddarth Jain
Siddarth's Quick Links

  • Biography

    Siddarth's research lies at the intersection of robotics, computer vision, and machine learning. His doctoral thesis investigated mathematical models for probabilistic human intent recognition, shared autonomy for assistive human-robot systems, and perception algorithms involving point cloud processing with geometric methods and machine learning. Prior to joining MERL in 2019, he was affiliated with the Shirley Ryan Abilitylab, Chicago (nation's top ranked physical medicine and rehabilitation research hospital) where his research lead to developments in the assistive robotics domain, involving user studies and interactive robotic systems that integrate perception, machine learning, planning, and control to act with people in practical applications. Currently, Siddarth's research focuses on the core challenges in active perception, robotic manipulation, autonomy, and human-robot interaction.

  • Recent News & Events

    •  NEWS    MERL at the International Conference on Robotics and Automation (ICRA) 2024
      Date: May 13, 2024 - May 17, 2024
      Where: Yokohama, Japan
      MERL Contacts: Anoop Cherian; Radu Corcodel; Stefano Di Cairano; Chiori Hori; Siddarth Jain; Devesh K. Jha; Jonathan Le Roux; Diego Romeres; William S. Yerazunis
      Research Areas: Artificial Intelligence, Machine Learning, Optimization, Robotics, Speech & Audio
      Brief
      • MERL made significant contributions to both the organization and the technical program of the International Conference on Robotics and Automation (ICRA) 2024, which was held in Yokohama, Japan from May 13th to May 17th.

        MERL was a Bronze sponsor of the conference, and exhibited a live robotic demonstration, which attracted a large audience. The demonstration showcased an Autonomous Robotic Assembly technology executed on MELCO's Assista robot arm and was the collaborative effort of the Optimization and Robotics Team together with the Advanced Technology department at Mitsubishi Electric.

        MERL researchers from the Optimization and Robotics, Speech & Audio, and Control for Autonomy teams also presented 8 papers and 2 invited talks covering topics on robotic assembly, applications of LLMs to robotics, human robot interaction, safe and robust path planning for autonomous drones, transfer learning, perception and tactile sensing.
    •  
    •  TALK    [MERL Seminar Series 2024] Stefanos Nikolaidis presents talk titled Enhancing the Efficiency and Robustness of Human-Robot Interactions
      Date & Time: Friday, March 8, 2024; 1:00 PM
      Speaker: Stefanos Nikolaidis, University of Southern California
      MERL Host: Siddarth Jain
      Research Areas: Machine Learning, Robotics, Human-Computer Interaction
      Abstract
      • While robots have been successfully deployed in factory floors and warehouses, there has been limited progress in having them perform physical tasks with people at home and in the workplace. I aim to bridge the gap between their current performance in human environments and what robots are capable of doing, by making human-robot interactions efficient and robust.

        In the first part of my talk, I discuss enhancing the efficiency of human-robot interactions by enabling robot manipulators to infer the preference of a human teammate and proactively assist them in a collaborative task. I show how we can leverage similarities between different users and tasks to learn compact representations of user preferences and use these representations as priors for efficient inference.

        In the second part, I talk about enhancing the robustness of human-robot interactions by algorithmically generating diverse and realistic scenarios in simulation that reveal system failures. I propose formulating the problem of algorithmic scenario generation as a quality diversity problem and show how standard quality diversity algorithms can discover surprising and unexpected failure cases. I then discuss the development of a new class of quality diversity algorithms that significantly improve the search of the scenario space and the integration of these algorithms with generative models, which enables the generation of complex and realistic scenarios.

        Finally, I conclude the talk with applications in mining operations, collaborative manufacturing and assistive care.
    •  

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  • Awards

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  • Internships with Siddarth

    • OR0087: Internship - Human-Robot Collaboration with Shared Autonomy

      MERL is looking for a highly motivated and qualified intern to contribute to research in human-robot interaction (HRI). The ideal candidate is a Ph.D. student with expertise in robotic manipulation, perception, deep learning, probabilistic modeling, or reinforcement learning. We have several research topics available, including assistive teleoperation, visual scene reconstruction, safety in HRI, shared autonomy, intent recognition, cooperative manipulation, and robot learning. The selected intern will work closely with MERL researchers to develop and implement novel algorithms, conduct experiments, and present research findings. We publish our research at top-tier conferences. Start date is flexible, and the expected duration of the internship is 3-4 months. Interested candidates are encouraged to apply with their updated CV and list of publications.

      Required Specific Experience

      • Experience with ROS and deep learning frameworks such as PyTorch are essential.
      • Strong programming skills in Python and/or C/C++
      • Experience with simulation tools, such as PyBullet, Issac Lab, or MuJoCo.
      • Prior experience in human-robot interaction, perception, or robotic manipulation.

    • OR0127: Internship - Deep Learning for Robotic Manipulation

      MERL is looking for a highly motivated and qualified intern to work on deep learning methods for detection and pose estimation of objects using vision and tactile sensing, in manufacturing and assembly environments. This role involves developing, fine-tuning and deploying models on existing hardware. The method will be applied for robotic manipulation where the knowledge of accurate position and orientation of objects within the scene would allow the robot to interact with the objects. The ideal candidate would be a Ph.D. student familiar with the state-of-the-art methods for pose estimation and tracking of objects. The successful candidate will work closely with MERL researchers to develop and implement novel algorithms, conduct experiments, and publish research findings at a top-tier conference. Start date and expected duration of the internship is flexible. Interested candidates are encouraged to apply with their updated CV and list of relevant publications.

      Required Specific Experience

      • Prior experience in Computer Vision and Robotic Manipulation.
      • Experience with ROS and deep learning frameworks such as PyTorch are essential.
      • Strong programming skills in Python.
      • Experience with simulation tools, such as PyBullet, Issac Lab, or MuJoCo.

    See All Internships at MERL

  • MERL Publications

    •  Suresh, P., Romeres, D., Dosh, P., Jain, S., "Open Human-Robot Collaboration Systems (OHRCS): A Research Perspective", IEEE International Conference on Cognitive Machine Intelligence (CogML 2024), October 2024.
      BibTeX TR2024-150 PDF
      • @inproceedings{Suresh2024nov,
      • author = {{Suresh, Prasanth and Romeres, Diego and Dosh, Prashant and Jain, Siddarth}},
      • title = {Open Human-Robot Collaboration Systems (OHRCS): A Research Perspective},
      • booktitle = {IEEE International Conference on Cognitive Machine Intelligence (CogML 2024)},
      • year = 2024,
      • month = oct,
      • url = {https://www.merl.com/publications/TR2024-150}
      • }
    •  Giacomuzzo, G., Terreran, M., Jain, S., Romeres, D., "DECAF: a Discrete-Event based Collaborative Human-Robot Framework for Furniture Assembly", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2024.
      BibTeX TR2024-138 PDF
      • @inproceedings{Giacomuzzo2024oct,
      • author = {Giacomuzzo, Giulio and Terreran, Matteo and Jain, Siddarth and Romeres, Diego}},
      • title = {DECAF: a Discrete-Event based Collaborative Human-Robot Framework for Furniture Assembly},
      • booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
      • year = 2024,
      • month = oct,
      • url = {https://www.merl.com/publications/TR2024-138}
      • }
    •  Chang, H., Boularias, A., Jain, S., "Insert-One: One-Shot Robust Visual-Force Servoing for Novel Object Insertion with 6-DoF Tracking", 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024), October 2024.
      BibTeX TR2024-137 PDF
      • @inproceedings{Chang2024oct,
      • author = {Chang, Haonan and Boularias, Abdeslam and Jain, Siddarth}},
      • title = {Insert-One: One-Shot Robust Visual-Force Servoing for Novel Object Insertion with 6-DoF Tracking},
      • booktitle = {2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024)},
      • year = 2024,
      • month = oct,
      • url = {https://www.merl.com/publications/TR2024-137}
      • }
    •  Suresh, P., Jain, S., Doshi, P., Romeres, D., "Open Human-Robot Collaboration using Decentralized Inverse Reinforcement Learning", 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024), October 2024.
      BibTeX TR2024-135 PDF
      • @inproceedings{Suresh2024oct,
      • author = {Suresh, Prasanth and Jain, Siddarth and Doshi, Prashant and Romeres, Diego}},
      • title = {Open Human-Robot Collaboration using Decentralized Inverse Reinforcement Learning},
      • booktitle = {2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024)},
      • year = 2024,
      • month = oct,
      • url = {https://www.merl.com/publications/TR2024-135}
      • }
    •  Ota, K., Jha, D.K., Jain, S., Yerazunis, W.S., Corcodel, R., Shukla, Y., Bronars, A., Romeres, D., "Autonomous Robotic Assembly: From Part Singulation to Precise Assembly", IEEE/RSJ International Conference on Intelligent Robots and Systems., October 2024.
      BibTeX TR2024-133 PDF
      • @inproceedings{Ota2024oct,
      • author = {Ota, Kei and Jha, Devesh K. and Jain, Siddarth and Yerazunis, William S. and Corcodel, Radu and Shukla, Yash and Bronars, Antonia and Romeres, Diego}},
      • title = {Autonomous Robotic Assembly: From Part Singulation to Precise Assembly},
      • booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems.},
      • year = 2024,
      • month = oct,
      • url = {https://www.merl.com/publications/TR2024-133}
      • }
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  • Other Publications

    •  Siddarth Jain and Brenna Argall, "Probabilistic Human Intent Recognition for Shared Autonomy in Assistive Robotics", ACM Transactions on Human-Robot Interaction (THRI), 2019.
      BibTeX
      • @Article{jain2019intent,
      • author = {Jain, Siddarth and Argall, Brenna},
      • title = {Probabilistic Human Intent Recognition for Shared Autonomy in Assistive Robotics},
      • booktitle = {ACM Transactions on Human-Robot Interaction (THRI)},
      • year = 2019,
      • organization = {ACM}
      • }
    •  Siddarth Jain and Brenna Argall, "Recursive Bayesian Human Intent Recognition in Shared-Control Robotics", In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018.
      BibTeX
      • @Inproceedings{jain2018recursive,
      • author = {Jain, Siddarth and Argall, Brenna},
      • title = {Recursive Bayesian Human Intent Recognition in Shared-Control Robotics},
      • booktitle = {In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
      • year = 2018,
      • organization = {IEEE}
      • }
    •  Deepak Gopinath, Siddarth Jain and Brenna D Argall, "Human-in-the-loop optimization of shared autonomy in assistive robotics", IEEE robotics and automation letters, Vol. 2, No. 1, pp. 247-254, 2016.
      BibTeX
      • @Article{gopinath2016human,
      • author = {Gopinath, Deepak and Jain, Siddarth and Argall, Brenna D},
      • title = {Human-in-the-loop optimization of shared autonomy in assistive robotics},
      • journal = {IEEE robotics and automation letters},
      • year = 2016,
      • volume = 2,
      • number = 1,
      • pages = {247--254},
      • publisher = {IEEE}
      • }
    •  Siddarth Jain and Brenna Argall, "Grasp detection for assistive robotic manipulation", In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2016.
      BibTeX
      • @Inproceedings{jain2016grasp,
      • author = {Jain, Siddarth and Argall, Brenna},
      • title = {Grasp detection for assistive robotic manipulation},
      • booktitle = {In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)},
      • year = 2016,
      • organization = {IEEE}
      • }
    •  Siddarth Jain, Ali Farshchiansadegh, Alexander Broad, Farnaz Abdollahi, Ferdinando Mussa-Ivaldi and Brenna Argall, "Assistive robotic manipulation through shared autonomy and a body-machine interface", In Proceedings of the IEEE international conference on rehabilitation robotics (ICORR), 2015.
      BibTeX
      • @Inproceedings{jain2015assistive,
      • author = {Jain, Siddarth and Farshchiansadegh, Ali and Broad, Alexander and Abdollahi, Farnaz and Mussa-Ivaldi, Ferdinando and Argall, Brenna},
      • title = {Assistive robotic manipulation through shared autonomy and a body-machine interface},
      • booktitle = {In Proceedings of the IEEE international conference on rehabilitation robotics (ICORR)},
      • year = 2015,
      • organization = {IEEE}
      • }
    •  Siddarth Jain, Katherine A Barsness and Brenna Argall, "Automated and objective assessment of surgical training: detection of procedural steps on videotaped performances", In Proceedings of the International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2015.
      BibTeX
      • @Inproceedings{jain2015automated,
      • author = {Jain, Siddarth and Barsness, Katherine A and Argall, Brenna},
      • title = {Automated and objective assessment of surgical training: detection of procedural steps on videotaped performances},
      • booktitle = {In Proceedings of the International Conference on Digital Image Computing: Techniques and Applications (DICTA)},
      • year = 2015,
      • organization = {IEEE}
      • }
    •  Siddarth Jain and Brenna Argall, "Automated perception of safe docking locations with alignment information for assistive wheelchairs", In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2014.
      BibTeX
      • @Inproceedings{jain2014automated,
      • author = {Jain, Siddarth and Argall, Brenna},
      • title = {Automated perception of safe docking locations with alignment information for assistive wheelchairs},
      • booktitle = {In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
      • year = 2014,
      • organization = {IEEE}
      • }

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  • MERL Issued Patents

    • Title: "Simulation-in-the-loop Tuning of Robot Parameters for System Modeling and Control"
      Inventors: Jain, Siddarth; Van Baar, Jeroen; Corcodel, Radu Ioan; Sullivan, Alan; Benosman, Mouhacine
      Patent No.: 11,975,451
      Issue Date: May 7, 2024
    • Title: "Interactive Tactile Perception Method for Classification and Recognition of Object Instances"
      Inventors: Corcodel, Radu Ioan; Jain, Siddarth; van Baar, Jeroen
      Patent No.: 11,794,350
      Issue Date: Oct 24, 2023
    See All Patents for MERL