Dynamical Systems
Exploiting nonlinearity and shaping dynamics in creative and deeply mathematical ways.
We apply dynamical systems theory in applications ranging from space probe trajectory optimization to elevator suspensions. We also develop fundamental theory and computational methods in fluid dynamics.
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Researchers
Stefano
Di Cairano
Avishai
Weiss
Yebin
Wang
Abraham P.
Vinod
Scott A.
Bortoff
Christopher R.
Laughman
Saviz
Mowlavi
Ankush
Chakrabarty
Hassan
Mansour
Petros T.
Boufounos
Hongtao
Qiao
Daniel N.
Nikovski
Purnanand
Elango
Chungwei
Lin
Abraham
Goldsmith
Devesh K.
Jha
Yanting
Ma
Diego
Romeres
Pedro
Miraldo
Philip V.
Orlik
Arvind
Raghunathan
Alexander
Schperberg
Pu
(Perry)
Wang
William S.
Yerazunis
Vedang M.
Deshpande
Jianlin
Guo
Toshiaki
Koike-Akino
Kieran
Parsons
Joshua
Rapp
Hongbo
Sun
Bingnan
Wang
Jinyun
Zhang
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Awards
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AWARD University of Padua and MERL team wins the AI Olympics with RealAIGym competition at IROS24 Date: October 17, 2024
Awarded to: Niccolò Turcato, Alberto Dalla Libera, Giulio Giacomuzzo, Ruggero Carli, Diego Romeres
MERL Contact: Diego Romeres
Research Areas: Artificial Intelligence, Dynamical Systems, Machine Learning, RoboticsBrief- The team composed of the control group at the University of Padua and MERL's Optimization and Robotic team ranked 1st out of the 4 finalist teams that arrived to the 2nd AI Olympics with RealAIGym competition at IROS 24, which focused on control of under-actuated robots. The team was composed by Niccolò Turcato, Alberto Dalla Libera, Giulio Giacomuzzo, Ruggero Carli and Diego Romeres. The competition was organized by the German Research Center for Artificial Intelligence (DFKI), Technical University of Darmstadt and Chalmers University of Technology.
The competition and award ceremony was hosted by IEEE International Conference on Intelligent Robots and Systems (IROS) on October 17, 2024 in Abu Dhabi, UAE. Diego Romeres presented the team's method, based on a model-based reinforcement learning algorithm called MC-PILCO.
- The team composed of the control group at the University of Padua and MERL's Optimization and Robotic team ranked 1st out of the 4 finalist teams that arrived to the 2nd AI Olympics with RealAIGym competition at IROS 24, which focused on control of under-actuated robots. The team was composed by Niccolò Turcato, Alberto Dalla Libera, Giulio Giacomuzzo, Ruggero Carli and Diego Romeres. The competition was organized by the German Research Center for Artificial Intelligence (DFKI), Technical University of Darmstadt and Chalmers University of Technology.
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AWARD MERL’s Paper on Wi-Fi Sensing Earns Top 3% Paper Recognition at ICASSP 2023, Selected as a Best Student Paper Award Finalist Date: June 9, 2023
Awarded to: Cristian J. Vaca-Rubio, Pu Wang, Toshiaki Koike-Akino, Ye Wang, Petros Boufounos and Petar Popovski
MERL Contacts: Petros T. Boufounos; Toshiaki Koike-Akino; Pu (Perry) Wang; Ye Wang
Research Areas: Artificial Intelligence, Communications, Computational Sensing, Dynamical Systems, Machine Learning, Signal ProcessingBrief- A MERL Paper on Wi-Fi sensing was recognized as a Top 3% Paper among all 2709 accepted papers at the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023). Co-authored by Cristian Vaca-Rubio and Petar Popovski from Aalborg University, Denmark, and MERL researchers Pu Wang, Toshiaki Koike-Akino, Ye Wang, and Petros Boufounos, the paper "MmWave Wi-Fi Trajectory Estimation with Continous-Time Neural Dynamic Learning" was also a Best Student Paper Award finalist.
Performed during Cristian’s stay at MERL first as a visiting Marie Skłodowska-Curie Fellow and then as a full-time intern in 2022, this work capitalizes on standards-compliant Wi-Fi signals to perform indoor localization and sensing. The paper uses a neural dynamic learning framework to address technical issues such as low sampling rate and irregular sampling intervals.
ICASSP, a flagship conference of the IEEE Signal Processing Society (SPS), was hosted on the Greek island of Rhodes from June 04 to June 10, 2023. ICASSP 2023 marked the largest ICASSP in history, boasting over 4000 participants and 6128 submitted papers, out of which 2709 were accepted.
- A MERL Paper on Wi-Fi sensing was recognized as a Top 3% Paper among all 2709 accepted papers at the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023). Co-authored by Cristian Vaca-Rubio and Petar Popovski from Aalborg University, Denmark, and MERL researchers Pu Wang, Toshiaki Koike-Akino, Ye Wang, and Petros Boufounos, the paper "MmWave Wi-Fi Trajectory Estimation with Continous-Time Neural Dynamic Learning" was also a Best Student Paper Award finalist.
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News & Events
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NEWS MERL researchers present 13 papers at ACC 2025 Date: July 8, 2025 - July 10, 2025
Where: Denver, USA
MERL Contacts: Ankush Chakrabarty; Vedang M. Deshpande; Stefano Di Cairano; Purnanand Elango; Jordan Leung; Saviz Mowlavi; Diego Romeres; Abraham P. Vinod; Yebin Wang; Avishai Weiss
Research Areas: Control, Dynamical Systems, Electric Systems, Machine Learning, Multi-Physical Modeling, RoboticsBrief- MERL researchers presented 13 papers at the recently concluded American Control Conference (ACC) 2025 in Denver, USA. The papers covered a wide range of topics including Bayesian optimization for personalized medicine, machine learning for battery performance in eVTOLs, model predictive control for space and building systems, process systems engineering for sustainability, GNSS-RTK optimization, convex set manipulation, PDE control, servo system modeling, battery fault diagnosis, truck fleet coordination, interactive motion planning, and satellite station keeping. Additionally, MERL researchers (Vedang Deshpande and Ankush Chakrabarty) organized an invited session on design and optimization of energy systems.
As a sponsor of the conference, MERL maintained a booth for open discussions with researchers and students, and hosted a special session to discuss highlights of MERL research and work philosophy.
- MERL researchers presented 13 papers at the recently concluded American Control Conference (ACC) 2025 in Denver, USA. The papers covered a wide range of topics including Bayesian optimization for personalized medicine, machine learning for battery performance in eVTOLs, model predictive control for space and building systems, process systems engineering for sustainability, GNSS-RTK optimization, convex set manipulation, PDE control, servo system modeling, battery fault diagnosis, truck fleet coordination, interactive motion planning, and satellite station keeping. Additionally, MERL researchers (Vedang Deshpande and Ankush Chakrabarty) organized an invited session on design and optimization of energy systems.
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NEWS MERL contributes to 2025 European Control Conference Date: June 24, 2025 - June 27, 2025
Where: Thessaloniki
MERL Contacts: Stefano Di Cairano; Daniel N. Nikovski; Diego Romeres; Yebin Wang
Research Areas: Control, Dynamical Systems, Machine Learning, Multi-Physical Modeling, Optimization, RoboticsBrief- MERL researchers contributed to both the technical program and workshop organization at the 2025 European Control Conference (ECC), held in Thessaloniki, Greece, from June 24 to 27. ECC is one of the premier conferences in the field of control.
In the main conference, MERL researchers presented four papers covering a range of topics, including: Representation learning, Motion planning for tractor-trailers, Motion planning for mobile manipulators, Learning high-dimensional dynamical systems, Model learning for robotics.
Additionally, MERL co-organized a workshop with the University of Padua titled “Reinforcement Learning for Robotic Control: Recent Developments and Open Challenges.” MERL researcher Diego Romeres also delivered an invited talk titled “Human-Robot Collaborative Assembly” in that workshop.
- MERL researchers contributed to both the technical program and workshop organization at the 2025 European Control Conference (ECC), held in Thessaloniki, Greece, from June 24 to 27. ECC is one of the premier conferences in the field of control.
See All News & Events for Dynamical Systems -
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Internships
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CA0166: Internship - Spacecraft Guidance, Navigation, and Control
MERL is seeking a highly motivated graduate student for a research position in guidance, navigation, and control of spacecraft. The ideal candidate is a PhD student with strong experience in trajectory generation and sequential convex optimization, stochastic optimal control and state estimation, and astrodynamics and the three-body problem. Publication of results produced during the internship is expected. The expected duration of the internship is 3-6 months with a flexible start date.
Required Specific Experience
- Current enrollment in a PhD program in Aerospace, Mechanical, Electrical Engineering, or a related field
- Familiarity with convex optimization solvers
- Strong programming skills in Matlab, Python, and/or C/C++
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CA0170: Internship - Offroad Quadruped Robots
MERL is seeking a highly motivated intern to collaborate in the development of outdoor, offroad applications of quadruped robots, with wildlife monitoring and farming as examples. The overall project involves multiple developments including robust gait control, optimal gait generation in uncertain terrain conditions, planning and allocation of multiple robots. The work will be validated in simulation first, and experimental validation will be possible (if time permits) on robotic platforms on-site. The results of the internship are expected to be published in top-tier conferences and/or journals. The internship will take place during Fall/Winter 2025 (exact dates are flexible) with an expected duration of 3-6 months.
Please use your cover letter to explain how you meet the following requirements, preferably with links to papers, code repositories, etc., indicating your proficiency.
Required Experience
- Current enrollment in a PhD program in Mechanical, Electrical, Aerospace Engineering, Computer Science or related programs, with a focus on Robotics and/or Control Systems
- Experience in some/all of these topics:
- Planning and control for legged robots
- Modeling and control in offroad scenarios
- ROS and simulation environment for robots control,
- Strong programming skills in Python and/or C/C++
Additional Useful Experience
- Modeling of terrain uncertaint
- Robust control and planning under uncertainty
- Coverage control in uncertain scenarios
- Experience with computer vision
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CA0165: Internship - Optimization of Aerial Robot Coordination
MERL is seeking a self-motivated and qualified individual to work on developing an integer/mixed-integer programming solver customarily designed for coordination planning of aerial drones. The ideal candidate will be a PhD student in computer science, mathematics, industrial engineering, or a related discipline, with a solid background in integer optimization. Preferred skills include knowledge of branch-price-and-cut algorithm or column generation, and hands-on experience with callbacks of the Gurobi Optimizer; strong programming skills and experience with at least one of Python, Julia, C/C++, Matlab are also expected. Publication of results produced during the internship is desired. The expected start date is in Fall 2025 or Spring 2026, for a duration of 3- months.
Required Specific Experience
- Significant hands-on experience with integer optimization.
- Experience with trajectory optimization is a plus.
- Fluency in at least one of: Python, Julia, C/C++, Matlab
- Completed their MS, or >30% of their PhD program
- Significant hands-on experience with integer optimization.
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Openings
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Recent Publications
- , "Dynamic Sensor Scheduling for Spatio-temporal Monitoring of Water Bodies", IEEE Conference on Control Technology and Applications (CCTA), August 2025.BibTeX TR2025-117 PDF
- @inproceedings{Deshpande2025aug,
- author = {Deshpande, Vedang M. and Vinod, Abraham P.},
- title = {{Dynamic Sensor Scheduling for Spatio-temporal Monitoring of Water Bodies}},
- booktitle = {IEEE Conference on Control Technology and Applications (CCTA)},
- year = 2025,
- month = aug,
- url = {https://www.merl.com/publications/TR2025-117}
- }
- , "Multi-Band Wi-Fi Neural Dynamic Fusion", IEEE Transactions on Wireless Communications, July 2025.BibTeX TR2025-115 PDF
- @article{Kato2025jul,
- author = {Kato, Sorachi and Wang, Pu and Koike-Akino, Toshiaki and Fujihashi, Takuya and Mansour, Hassan and Boufounos, Petros T.},
- title = {{Multi-Band Wi-Fi Neural Dynamic Fusion}},
- journal = {IEEE Transactions on Wireless Communications},
- year = 2025,
- month = jul,
- url = {https://www.merl.com/publications/TR2025-115}
- }
- , "Policy Optimization for PDE Control with a Warm Start", American Control Conference (ACC), July 2025.BibTeX TR2025-105 PDF
- @inproceedings{Zhang2025jul,
- author = {Zhang, Xiangyuan and Mowlavi, Saviz and Benosman, Mouhacine and Basar, Tamer},
- title = {{Policy Optimization for PDE Control with a Warm Start}},
- booktitle = {American Control Conference (ACC)},
- year = 2025,
- month = jul,
- url = {https://www.merl.com/publications/TR2025-105}
- }
- , "Truck Fleet Coordination for Warehouse Trailer Management by Temporal Logic with Energy Constraints", American Control Conference (ACC), July 2025.BibTeX TR2025-103 PDF
- @inproceedings{Cardona2025jul,
- author = {Cardona, Gustavo and Vasile, Cristian-Ioan and {Di Cairano}, Stefano},
- title = {{Truck Fleet Coordination for Warehouse Trailer Management by Temporal Logic with Energy Constraints}},
- booktitle = {American Control Conference (ACC)},
- year = 2025,
- month = jul,
- url = {https://www.merl.com/publications/TR2025-103}
- }
- , "Safe Interactive Motion Planning by Differentiable Optimal Control and Online Preference Learning", American Control Conference (ACC), July 2025.BibTeX TR2025-104 PDF
- @inproceedings{ChavezArmijos2025jul,
- author = {Chavez Armijos, Andres and Berntorp, Karl and {Di Cairano}, Stefano},
- title = {{Safe Interactive Motion Planning by Differentiable Optimal Control and Online Preference Learning}},
- booktitle = {American Control Conference (ACC)},
- year = 2025,
- month = jul,
- url = {https://www.merl.com/publications/TR2025-104}
- }
- , "GNSS-RTK Factor Graph Optimization with Adaptive Ambiguity Noise", American Control Conference (ACC), July 2025.BibTeX TR2025-102 PDF
- @inproceedings{Hu2025jul,
- author = {Hu, Yingjie and {Di Cairano}, Stefano and Berntorp, Karl},
- title = {{GNSS-RTK Factor Graph Optimization with Adaptive Ambiguity Noise}},
- booktitle = {American Control Conference (ACC)},
- year = 2025,
- month = jul,
- url = {https://www.merl.com/publications/TR2025-102}
- }
- , "Geostationary Satellite Station Keeping and Collocation under High-Thrust Impulsive Control", American Control Conference (ACC), July 2025.BibTeX TR2025-101 PDF
- @inproceedings{Pavlasek2025jul,
- author = {Pavlasek, Natalia and {Di Cairano}, Stefano and Weiss, Avishai},
- title = {{Geostationary Satellite Station Keeping and Collocation under High-Thrust Impulsive Control}},
- booktitle = {American Control Conference (ACC)},
- year = 2025,
- month = jul,
- url = {https://www.merl.com/publications/TR2025-101}
- }
- , "Station-Keeping on Near-Rectilinear Halo Orbits via Full-State Targeting Model Predictive Control", American Control Conference (ACC), July 2025.BibTeX TR2025-100 PDF
- @inproceedings{Shimane2025jul,
- author = {Shimane, Yuri and {Di Cairano}, Stefano and Ho, Koki and Weiss, Avishai},
- title = {{Station-Keeping on Near-Rectilinear Halo Orbits via Full-State Targeting Model Predictive Control}},
- booktitle = {American Control Conference (ACC)},
- year = 2025,
- month = jul,
- url = {https://www.merl.com/publications/TR2025-100}
- }
- , "Dynamic Sensor Scheduling for Spatio-temporal Monitoring of Water Bodies", IEEE Conference on Control Technology and Applications (CCTA), August 2025.
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