Diego Romeres
- Phone: 617-621-7561
- Email:
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Position:
Research / Technical Staff
Principal Research Scientist -
Education:
Ph.D., University of Padova, 2017 -
Research Areas:
External Links:
Diego's Quick Links
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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.
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Recent News & Events
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NEWS Diego Romeres appointed as an Associate Editor for IROS 2021 Date: March 14, 2021 - April 20, 2021
Where: IROS
MERL Contact: Diego Romeres
Research Areas: Artificial Intelligence, Data Analytics, RoboticsBrief- Diego Romeres, a Principal Research Scientist in MERL's Data Analytics group, is serving as an Associate Editor (AE) for the 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2021).
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NEWS Diego Romeres gave an invited talk at the Autonomy Talks at ETH, Zurich. Date: February 15, 2021
Where: Virtual
MERL Contact: Diego Romeres
Research Areas: Artificial Intelligence, Machine Learning, RoboticsBrief- Diego Romeres, a Principal Research Scientist in MERL's Data Analytics group, gave the invited talk "Reinforcement Learning for Robotics" at the Autonomy Talks organized at ETH, Zurich. In the presentation, some directions to apply Model-based Reinforcement Learning algorithms to real-world applications are presented together with a novel MBRL algorithm called MC-PILCO. The link to the presentation is https://www.youtube.com/watch?v=wYgbgMa4j-s.
See All News & Events for Diego -
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Internships with Diego
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DA1602: Reinforcement Learning for HVAC systems
MERL is looking for a self-motivated and qualified candidate to work on air flow control of Heating, Ventilation and Air Conditioning (HVAC) systems. The ideal candidate is a PhD student and should have experience and records in multiple of the following areas: fluid dynamics, control theory, reinforcement learning, familiarity with partial differential equations. Proficiency in Python and Matlab is required. The successful candidate will be expected to develop, in collaboration with MERL employees, a state of the art algorithms for air flow control that will lead to a scientific publication. Typical internship length is 3 months. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.
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MERL Publications
- , "Personalizing Individual Comfort in the Group Setting", Tech. Rep. TR2021-011, Mitsubishi Electric Research Laboratories, Cambridge, MA, March 2021.BibTeX TR2021-011 PDF
- @techreport{MERL_TR2021-011,
- author = {Laftchiev, Emil; Romeres, Diego; Nikovski, Daniel N.},
- title = {Personalizing Individual Comfort in the Group Setting},
- institution = {MERL - Mitsubishi Electric Research Laboratories},
- address = {Cambridge, MA 02139},
- number = {TR2021-011},
- month = mar,
- year = 2021,
- url = {https://www.merl.com/publications/TR2021-011/}
- }
- , "Model-Based Policy Search Using Monte Carlo Gradient Estimation with Real Systems Application", arXiv, February 2021.BibTeX
- @article{Romeres2021feb,
- author = {Romeres, Diego and Amadio, Fabio and Dalla Libera, Alberto and Antonello, Riccardo and Carli, Ruggero and Nikovski, Daniel N.},
- title = {Model-Based Policy Search Using Monte Carlo Gradient Estimation with Real Systems Application},
- journal = {arXiv},
- year = 2021,
- month = feb
- }
- , "Towards Human-Level Learning of Complex Physical Puzzles", arXiv, December 2020.BibTeX
- @article{Ota2020dec,
- author = {Ota, Kei and Jha, Devesh and Romeres, Diego and van Baar, Jeroen and Smith, Kevin and Semistsu, Takayuki and Oiki, Tomoaki and Sullivan, Alan and Nikovski, Daniel N. and Tenanbaum, Joshua},
- title = {Towards Human-Level Learning of Complex Physical Puzzles},
- journal = {arXiv},
- year = 2020,
- month = dec
- }
- , "Model-based Policy Search for Partially Measurable Systems", Advances in Neural Information Processing Systems (NeurIPS), December 2020.BibTeX TR2020-174 PDF
- @inproceedings{Romeres2020dec2,
- author = {Romeres, Diego and Amadio, Fabio and Dalla Libera, Alberto and Nikovski, Daniel N. and Carli, Ruggero},
- title = {Model-based Policy Search for Partially Measurable Systems},
- booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
- year = 2020,
- month = dec,
- url = {https://www.merl.com/publications/TR2020-174}
- }
- , "Feedback Linearization Robot Control based on Gaussian Process Inverse Dynamics Model", Conferenza Italiana di Robotica e Macchine Intelligenti, December 2020.BibTeX TR2020-173 PDF
- @inproceedings{Romeres2020dec,
- author = {Romeres, Diego and Dalla Libera, Alberto and Amadio, Fabio and Carli, Ruggero},
- title = {Feedback Linearization Robot Control based on Gaussian Process Inverse Dynamics Model},
- booktitle = {Conferenza Italiana di Robotica e Macchine Intelligenti},
- year = 2020,
- month = dec,
- url = {https://www.merl.com/publications/TR2020-173}
- }
- , "Personalizing Individual Comfort in the Group Setting", Tech. Rep. TR2021-011, Mitsubishi Electric Research Laboratories, Cambridge, MA, March 2021.
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Other Publications
- , "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}
- }
- , "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}
- }
- , "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}
- }
- , "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}
- }
- , "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}
- }
- , "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}
- }
- , "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}
- }
- , "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}
- }
- , "On-line bayesian system identification", Control Conference (ECC), 2016 European, 2016, pp. 1359-1364.
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Software Downloads
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Videos
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Control of Mechanical Systems via Feedback Linearization Based on Black-Box Gaussian Process Models
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Towards Human-Level Learning of Complex Physical Puzzles
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Assembly of Belt Drive Units
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Examples of Robotic Manipulation
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Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry
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Monte Carlo Probabilistic Inference for Learning Control
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