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 MERL Researchers Presented Six Papers at the 2022 IEEE Conference on Decision and Control (CDC’22) Date: December 6, 2022 - December 9, 2022
Where: CancĂșn, Mexico
MERL Contacts: Mouhacine Benosman; Karl Berntorp; Ankush Chakrabarty; Marcus Greiff; Devesh K. Jha; Arvind Raghunathan; Diego Romeres; Yebin Wang
Research Areas: Control, OptimizationBrief- MERL researchers presented six papers at the Conference on Decision and Control that was held in CancĂșn, Mexico from December 6-9, 2022. The papers covered a broad range of topics in the areas of decision making and control, including Bayesian optimization, quadratic programming, solution of differential equations, distributed Kalman filtering, thermal monitoring of batteries, and closed-loop control optimization.
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NEWS MERL researchers presented 5 papers and an invited workshop talk at ICRA 2022 Date: May 23, 2022 - May 27, 2022
Where: International Conference on Robotics and Automation (ICRA)
MERL Contacts: Ankush Chakrabarty; Stefano Di Cairano; Siddarth Jain; Devesh K. Jha; Pedro Miraldo; Daniel N. Nikovski; Rien Quirynen; Arvind Raghunathan; Diego Romeres; Abraham P. Vinod; Yebin Wang
Research Areas: Artificial Intelligence, Machine Learning, RoboticsBrief- MERL researchers presented 5 papers at the IEEE International Conference on Robotics and Automation (ICRA) that was held in Philadelphia from May 23-27, 2022. The papers covered a broad range of topics from manipulation, tactile sensing, planning and multi-agent control. The invited talk was presented in the "Workshop on Collaborative Robots and Work of the Future" which covered some of the work done by MERL researchers on collaborative robotic assembly. The workshop was co-organized by MERL, Mitsubishi Electric Automation's North America Development Center (NADC), and MIT.
See All News & Events for Diego -
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Internships with Diego
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DA1956: Bayesian Optimization
MERL is looking for a self-motivated and qualified candidate to work on Bayesian Optimization for 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. An expected outcome of the internship is one or more peer-reviewed publications. Typical internship length is 3-4 months.
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MERL Publications
- "Learning Control from Raw Position Measurements", arXiv, January 2023. ,
- "Model-Based Policy Search Using Monte Carlo Gradient Estimation with Real Systems Application", IEEE Transaction on Robotics, DOI: 10.1109/TRO.2022.3184837, Vol. 38, No. 6, pp. 3879-3898, December 2022.BibTeX TR2022-154 PDF
- @article{Romeres2022dec,
- author = {Amadio, Fabio and Dalla Libera, Alberto and Antonello, Riccardo and Nikovski, Daniel N. and Carli, Ruggero and Romeres, Diego},
- title = {Model-Based Policy Search Using Monte Carlo Gradient Estimation with Real Systems Application},
- journal = {IEEE Transaction on Robotics},
- year = 2022,
- volume = 38,
- number = 6,
- pages = {3879--3898},
- month = dec,
- doi = {10.1109/TRO.2022.3184837},
- issn = {1941-0468},
- url = {https://www.merl.com/publications/TR2022-154}
- }
, - "Transfer Learning for Bayesian Optimization with Principal Component Analysis", International Conference on Machine Learning and Applications (ICMLA), December 2022.BibTeX TR2022-169 PDF
- @inproceedings{Masui2022dec,
- author = {Masui, Hideyuki and Romeres, Diego and Nikovski, Daniel N.},
- title = {Transfer Learning for Bayesian Optimization with Principal Component Analysis},
- booktitle = {International Conference on Machine Learning and Applications (ICMLA)},
- year = 2022,
- month = dec,
- url = {https://www.merl.com/publications/TR2022-169}
- }
, - "Homogeneous Infeasible Interior Point Method for Convex Quadratic Programs", IEEE Conference on Decision and Control (CDC), December 2022.BibTeX TR2022-157 PDF
- @inproceedings{Raghunathan2022dec,
- author = {Raghunathan, Arvind and Jha, Devesh K. and Romeres, Diego},
- title = {Homogeneous Infeasible Interior Point Method for Convex Quadratic Programs},
- booktitle = {IEEE Conference on Decision and Control (CDC)},
- year = 2022,
- month = dec,
- url = {https://www.merl.com/publications/TR2022-157}
- }
, - "Generalizable Human-Robot Collaborative Assembly Using Imitation Learning and Force Control", arXiv, December 2022.BibTeX arXiv
- @article{Jha2022dec,
- author = {Jha, Devesh K. and Jain, Siddarth and Romeres, Diego and Yerazunis, William S. and Nikovski, Daniel},
- title = {Generalizable Human-Robot Collaborative Assembly Using Imitation Learning and Force Control},
- journal = {arXiv},
- year = 2022,
- month = dec,
- url = {https://arxiv.org/abs/2212.01434}
- }
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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}
- }
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- "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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MERL Issued Patents
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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 N.
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.: 11,280514
Issue Date: Mar 22, 2022 -
Title: "System and Method for Automatic Error Recovery in Robotic Assembly"
Inventors: Nikovski, Daniel N.; Jha, Devesh; Romeres, Diego
Patent No.: 11,161,244
Issue Date: Nov 2, 2021
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Title: "Systems and Methods Automatic Anomaly Detection in Mixed Human-Robot Manufacturing Processes"