Diego Romeres

  • Biography

    Diego's research interests are in machine learning, system identification and robotic applications. At MERL he is currently working on applying nonparametric machine learning techniques for the control of robotic platforms. His Ph.D. thesis is about the combination of nonparametric data-driven models and physics-based models in gaussian processes for robot dynamics learning.

  • Recent News & Events


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  • Awards

    •  AWARD    Honorable Mention Award at NeurIPS 23 Instruction Workshop
      Date: December 15, 2023
      Awarded to: Lingfeng Sun, Devesh K. Jha, Chiori Hori, Siddharth Jain, Radu Corcodel, Xinghao Zhu, Masayoshi Tomizuka and Diego Romeres
      MERL Contacts: Radu Corcodel; Chiori Hori; Siddarth Jain; Devesh K. Jha; Diego Romeres
      Research Areas: Artificial Intelligence, Machine Learning, Robotics
      Brief
      • MERL Researchers received an "Honorable Mention award" at the Workshop on Instruction Tuning and Instruction Following at the NeurIPS 2023 conference in New Orleans. The workshop was on the topic of instruction tuning and Instruction following for Large Language Models (LLMs). MERL researchers presented their work on interactive planning using LLMs for partially observable robotic tasks during the oral presentation session at the workshop.
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    •  AWARD    Joint University of Padua-MERL team wins Challenge 'AI Olympics With RealAIGym'
      Date: August 25, 2023
      Awarded to: Alberto Dalla Libera, Niccolo' Turcato, Giulio Giacomuzzo, Ruggero Carli, Diego Romeres
      MERL Contact: Diego Romeres
      Research Areas: Artificial Intelligence, Machine Learning, Robotics
      Brief
      • A joint team consisting of members of University of Padua and MERL ranked 1st in the IJCAI2023 Challenge "Al Olympics With RealAlGym: Is Al Ready for Athletic Intelligence in the Real World?". The team was composed by MERL researcher Diego Romeres and a team from University Padua (UniPD) consisting of Alberto Dalla Libera, Ph.D., Ph.D. Candidates: Niccolò Turcato, Giulio Giacomuzzo and Prof. Ruggero Carli from University of Padua.

        The International Joint Conference on Artificial Intelligence (IJCAI) is a premier gathering for AI researchers and organizes several competitions. This year the competition CC7 "AI Olympics With RealAIGym: Is AI Ready for Athletic Intelligence in the Real World?" consisted of two stages: simulation and real-robot experiments on two under-actuated robotic systems. The two robotics systems were treated as separate tracks and one final winner was selected for each track based on specific performance criteria in the control tasks.

        The UniPD-MERL team competed and won in both tracks. The team's system made strong use of a Model-based Reinforcement Learning algorithm called (MC-PILCO) that we recently published in the journal IEEE Transaction on Robotics.
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  • Internships with Diego

    • OR2103: Human Robot Collaboration in Assembly Tasks

      MERL is looking for a self-motivated and qualified candidate to work on human-robot-interaction for manipulation and assembly collaborative scenarios. The ideal candidate is a PhD student and should have experience and records in one or multiple of the following areas. 1) Control, estimation and perception for Robotic manipulation 2) Task and Motion Planning 3) Learning from demonstration algorithms applied to robotic manipulation 4) Machine learning techniques for modeling and control as well as regression and classification problems. 5) Experience in working with robotic systems and familiarity with physics engine simulators like Mujoco, Isaac Gym, PyBullet. The successful candidate will be expected to develop, in collaboration with MERL employees, state of the art algorithms to solve complex manipulation tasks that involve human and robot collaborations. Proficiency in Python and ROS are required. The expectation is that the research will lead to one or more scientific publications. The expected duration s 3-4 months, with a flexible starting date.

    • OR2105: Preference-based Multi-Objective Bayesian Optimization

      MERL is looking for a self-motivated and qualified candidate to work on Bayesian Optimization algorithms applied to industrial applications. The ideal candidate is a PhD student with experience and peer-reviewed publications in the general field of derivative-free/zeroth-order optimization, preference will be given to candidates who have contributed to theoretical advances or practical application of Bayesian optimization, especially for multi-objective optimization problems. The ideal candidate will have a strong general understanding of numerical optimization and probabilistic machine learning e.g. Gaussian process regression, and is expected to develop, in collaboration with MERL researchers, state of the art algorithms to optimize parameters for industrial processes or control systems. Proficiency in Python is required. An expected outcome of the internship is one or more peer-reviewed publications. The expected duration is 3-4 months, with flexible starting date.

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  • MERL Publications

    •  Shirai, Y., Jha, D.K., Raghunathan, A., Romeres, D., "Chance-Constrained Optimization for Contact-rich Systems using Mixed Integer Programming", Nonlinear Analysis: Hybrid Systems, December 2024.
      BibTeX TR2024-008 PDF
      • @article{Shirai2024dec,
      • author = {Shirai, Yuki and Jha, Devesh K. and Raghunathan, Arvind and Romeres, Diego},
      • title = {Chance-Constrained Optimization for Contact-rich Systems using Mixed Integer Programming},
      • journal = {Nonlinear Analysis: Hybrid Systems},
      • year = 2024,
      • month = dec,
      • url = {https://www.merl.com/publications/TR2024-008}
      • }
    •  Zhu, X., Jha, D.K., Romeres, D., Sun, L., Tomizuka, M., Cherian, A., "Multi-level Reasoning for Robotic Assembly: From Sequence Inference to Contact Selection", arXiv, December 2023.
      BibTeX arXiv
      • @article{Zhu2023dec,
      • author = {Zhu, Xinghao and Jha, Devesh K. and Romeres, Diego and Sun, Lingfeng and Tomizuka, Masayoshi and Cherian, Anoop},
      • title = {Multi-level Reasoning for Robotic Assembly: From Sequence Inference to Contact Selection},
      • journal = {arXiv},
      • year = 2023,
      • month = dec,
      • url = {https://arxiv.org/abs/2312.10571}
      • }
    •  Sun, L., Jha, D.K., Hori, C., Jain, S., Corcodel, R., Zhu, X., Tomizuka, M., Romeres, D., "Interactive Planning Using Large Language Models for Partially Observable Robotics Tasks", Advances in Neural Information Processing Systems (NeurIPS) Workshop on Instruction Tuning and Instruction Following, December 2023.
      BibTeX TR2023-148 PDF
      • @inproceedings{Sun2023dec,
      • author = {Sun, Lingfeng and Jha, Devesh K. and Hori, Chiori and Jain, Siddarth and Corcodel, Radu and Zhu, Xinghao and Tomizuka, Masayoshi and Romeres, Diego},
      • title = {Interactive Planning Using Large Language Models for Partially Observable Robotics Tasks},
      • booktitle = {Advances in Neural Information Processing Systems (NeurIPS) Workshop on Instruction Tuning and Instruction Following},
      • year = 2023,
      • month = dec,
      • url = {https://www.merl.com/publications/TR2023-148}
      • }
    •  Shao, K., Romeres, D., Chakrabarty, A., Mesbah, A., "Preference-Guided Bayesian Optimization for Control Policy Learning: Application to Personalized Plasma Medicine", Advances in Neural Information Processing Systems (NeurIPS), December 2023.
      BibTeX TR2023-146 PDF
      • @inproceedings{Shao2023dec,
      • author = {Shao, Ketong and Romeres, Diego and Chakrabarty, Ankush and Mesbah, Ali},
      • title = {Preference-Guided Bayesian Optimization for Control Policy Learning: Application to Personalized Plasma Medicine},
      • booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
      • year = 2023,
      • month = dec,
      • url = {https://www.merl.com/publications/TR2023-146}
      • }
    •  Sun, L., Jha, D.K., Hori, C., Jain, S., Corcodel, R., Zhu, X., Tomizuka, M., Romeres, D., "Interactive Planning Using Large Language Models for Partially Observable Robotics Tasks", arXiv, December 2023.
      BibTeX arXiv
      • @article{Sun2023dec2,
      • author = {Sun, Lingfeng and Jha, Devesh K. and Hori, Chiori and Jain, Siddarth and Corcodel, Radu and Zhu, Xinghao and Tomizuka, Masayoshi and Romeres, Diego},
      • title = {Interactive Planning Using Large Language Models for Partially Observable Robotics Tasks},
      • journal = {arXiv},
      • year = 2023,
      • month = dec,
      • url = {https://arxiv.org/abs/2312.06876}
      • }
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  • Other Publications

    •  Diego Romeres, Giulia Prando, Gianluigi Pillonetto and Alessandro Chiuso, "On-line bayesian system identification", Control Conference (ECC), 2016 European, 2016, pp. 1359-1364.
      BibTeX
      • @Inproceedings{romeres2016line,
      • author = {Romeres, Diego and Prando, Giulia and Pillonetto, Gianluigi and Chiuso, Alessandro},
      • title = {On-line bayesian system identification},
      • booktitle = {Control Conference (ECC), 2016 European},
      • year = 2016,
      • pages = {1359--1364},
      • organization = {IEEE}
      • }
    •  Diego Romeres, Mattia Zorzi, Raffaello Camoriano and Alessandro Chiuso, "Online semi-parametric learning for inverse dynamics modeling", Decision and Control (CDC), 2016 IEEE 55th Conference on, 2016, pp. 2945-2950.
      BibTeX
      • @Inproceedings{romeres2016online,
      • author = {Romeres, Diego and Zorzi, Mattia and Camoriano, Raffaello and Chiuso, Alessandro},
      • title = {Online semi-parametric learning for inverse dynamics modeling},
      • booktitle = {Decision and Control (CDC), 2016 IEEE 55th Conference on},
      • year = 2016,
      • pages = {2945--2950},
      • organization = {IEEE}
      • }
    •  Diego Romeres, Mattia Zorzi, Raffaello Camoriano and Alessandro Chiuso, "Online semi-parametric learning for inverse dynamics modeling", Decision and Control (CDC), 2016 IEEE 55th Conference on, 2016, pp. 2945-2950.
      BibTeX
      • @Inproceedings{romeres2016onlinesemiparametric,
      • author = {Romeres, Diego and Zorzi, Mattia and Camoriano, Raffaello and Chiuso, Alessandro},
      • title = {Online semi-parametric learning for inverse dynamics modeling},
      • booktitle = {Decision and Control (CDC), 2016 IEEE 55th Conference on},
      • year = 2016,
      • pages = {2945--2950},
      • organization = {IEEE}
      • }
    •  Giulia Prando, Diego Romeres, Gianluigi Pillonetto and Alessandro Chiuso, "Classical vs. Bayesian methods for linear system identification: Point estimators and confidence sets", Control Conference (ECC), 2016 European, 2016, pp. 1365-1370.
      BibTeX
      • @Inproceedings{tprando2016classical,
      • author = {Prando, Giulia and Romeres, Diego and Pillonetto, Gianluigi and Chiuso, Alessandro},
      • title = {Classical vs. Bayesian methods for linear system identification: Point estimators and confidence sets},
      • booktitle = {Control Conference (ECC), 2016 European},
      • year = 2016,
      • pages = {1365--1370},
      • organization = {IEEE}
      • }
    •  Giulia Prando, Diego Romeres and Alessandro Chiuso, "Online identification of time-varying systems: A Bayesian approach", Decision and Control (CDC), 2016 IEEE 55th Conference on, 2016, pp. 3775-3780.
      BibTeX
      • @Inproceedings{tprando2016online,
      • author = {Prando, Giulia and Romeres, Diego and Chiuso, Alessandro},
      • title = {Online identification of time-varying systems: A Bayesian approach},
      • booktitle = {Decision and Control (CDC), 2016 IEEE 55th Conference on},
      • year = 2016,
      • pages = {3775--3780},
      • organization = {IEEE}
      • }
    •  Ulrich Muenz and Diego Romeres, "Region of attraction of power systems", IFAC Proceedings Volumes, Vol. 46, No. 27, pp. 49-54, 2013.
      BibTeX
      • @Article{munz2013region,
      • author = {Muenz, Ulrich and Romeres, Diego},
      • title = {Region of attraction of power systems},
      • journal = {IFAC Proceedings Volumes},
      • year = 2013,
      • volume = 46,
      • number = 27,
      • pages = {49--54},
      • publisher = {Elsevier}
      • }
    •  Diego Romeres, Florian Doerfler and Francesco Bullo, "Novel results on slow coherency in consensus and power networks", Control Conference (ECC), 2013 European, 2013, pp. 742-747.
      BibTeX
      • @Inproceedings{romeres2013novel,
      • author = {Romeres, Diego and Doerfler, Florian and Bullo, Francesco},
      • title = {Novel results on slow coherency in consensus and power networks},
      • booktitle = {Control Conference (ECC), 2013 European},
      • year = 2013,
      • pages = {742--747},
      • organization = {IEEE}
      • }
    •  Saverio Bolognani, Andrea Carron, Alberto Di Vittorio, Diego Romeres, Luca Schenato and Sandro Zampieri, "Distributed multi-hop reactive power compensation in smart micro-grids subject to saturation constraints", Decision and Control (CDC), 2012 IEEE 51st Annual Conference on, 2012, pp. 1118-1123.
      BibTeX
      • @Inproceedings{bolognani2012distributed,
      • author = {Bolognani, Saverio and Carron, Andrea and Di Vittorio, Alberto and Romeres, Diego and Schenato, Luca and Zampieri, Sandro},
      • title = {Distributed multi-hop reactive power compensation in smart micro-grids subject to saturation constraints},
      • booktitle = {Decision and Control (CDC), 2012 IEEE 51st Annual Conference on},
      • year = 2012,
      • pages = {1118--1123},
      • organization = {IEEE}
      • }
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  • MERL Issued Patents

    • Title: "OBJECT MANIPULATION WITH COLLISION AVOIDANCE USING COMPLEMENTARITY CONSTRAINTS"
      Inventors: Raghunathan, Arvind U; Jha, Devesh; Romeres, Diego
      Patent No.: 11,883,962
      Issue Date: Jan 30, 2024
    • Title: "System and Method for Robotic Assembly Based on Adaptive Compliance"
      Inventors: Nikovski, Daniel N.; Romeres, Diego; Jha, Devesh; Yerazunis, William S.
      Patent No.: 11,673,264
      Issue Date: Jun 13, 2023
    • Title: "System and Method for Policy Optimization using Quasi-Newton Trust Region Method"
      Inventors: Jha, Devesh; Raghunathan, Arvind U; Romeres, Diego
      Patent No.: 11,650,551
      Issue Date: May 16, 2023
    • Title: "Systems and Methods Automatic Anomaly Detection in Mixed Human-Robot Manufacturing Processes"
      Inventors: Laftchiev, Emil; Romeres, Diego
      Patent No.: 11,472,028
      Issue Date: Oct 18, 2022
    • Title: "Systems and Methods for Advance Anomaly Detection in a Discrete Manufacturing Process with a Task Performed by a Human-Robot Team"
      Inventors: Laftchiev, Emil; Romeres, Diego
      Patent No.: 11,442,429
      Issue Date: Sep 13, 2022
    • Title: "System and Design of Derivative-free Model Learning for Robotic Systems"
      Inventors: Romeres, Diego; Libera, Alberto Dalla; Jha, Devesh; Nikovski, Daniel Nikolaev
      Patent No.: 11,389,957
      Issue Date: Jul 19, 2022
    • Title: "System and Method for Thermal Control Based on Invertible Causation Relationship"
      Inventors: Laftchiev, Emil; Nikovski, Daniel N.; Romeres, Diego
      Patent No.: 11,280,514
      Issue Date: Mar 22, 2022
    • Title: "System and Method for Automatic Error Recovery in Robotic Assembly"
      Inventors: Nikovski, Daniel Nikolaev; Jha, Devesh; Romeres, Diego
      Patent No.: 11,161,244
      Issue Date: Nov 2, 2021
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