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
Karl
Berntorp
Mouhacine
Benosman
Yebin
Wang
Avishai
Weiss
Scott A.
Bortoff
Christopher R.
Laughman
Hongtao
Qiao
Abraham P.
Vinod
Ankush
Chakrabarty
Hassan
Mansour
Saviz
Mowlavi
Daniel N.
Nikovski
Petros T.
Boufounos
Abraham
Goldsmith
Chungwei
Lin
Devesh K.
Jha
Pedro
Miraldo
Philip V.
Orlik
Diego
Romeres
Jianlin
Guo
Yanting
Ma
Kieran
Parsons
Hongbo
Sun
Bingnan
Wang
Pu
(Perry)
WangWilliam S.
Yerazunis
Jinyun
Zhang
James
Queeney
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Awards
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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 Ankush Chakrabarty gave a lecture at UT-Austin's Seminar Series on Occupant-Centric Grid-Interactive Buildings Date: March 20, 2024
Where: Austin, TX
MERL Contact: Ankush Chakrabarty
Research Areas: Artificial Intelligence, Control, Data Analytics, Dynamical Systems, Machine Learning, Multi-Physical Modeling, OptimizationBrief- Ankush Chakrabarty, Principal Research Scientist in the Multiphysical Systems Team, was invited to speak as a guest lecturer in the seminar series on "Occupant-Centric Grid Interactive Buildings" in the Department of Civil, Architectural and Environmental Engineering (CAEE) at the University of Texas at Austin.
The talk, entitled "Deep Generative Networks and Fine-Tuning for Net-Zero Energy Buildings" described lessons learned from MERL's recent research on generative models for building simulation and control, along with meta-learning for on-the-fly fine-tuning to adapt and optimize energy expenditure.
- Ankush Chakrabarty, Principal Research Scientist in the Multiphysical Systems Team, was invited to speak as a guest lecturer in the seminar series on "Occupant-Centric Grid Interactive Buildings" in the Department of Civil, Architectural and Environmental Engineering (CAEE) at the University of Texas at Austin.
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NEWS Karl Berntorp joins the Editorial Board of IEEE Transactions on Control Systems Technology Date: December 7, 2023
MERL Contact: Karl Berntorp
Research Areas: Control, Dynamical SystemsBrief- Karl Berntorp has joined the Editorial Board of the IEEE Transactions on Control Systems Technology (T-CST) as an Associate Editor. The IEEE T-CST publishes peer-reviewed papers on technological advances in the design, realization, and operation of control systems, and bridges the gap between the theory and practice of control engineering.
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Internships
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CA2131: Collaborative Legged Robots
MERL is seeking a highly motivated and qualified intern to collaborate with the Control for Autonomy team in research on control and planning algorithms for legged robots for support activities of and collaboration with humans. The ideal candidate is expected to be working towards a PhD with strong emphasis in robotics control and planning and to have interest and background in as many as possible of: motion planning algorithms, control for legged robot locomotions, legged robots, perception and sensing with multiple sensors, SLAM, vision-based control. Good programming skills in Python or C/C++ are required. The expected start of of the internship is flexible, with duration of 3--6 months.
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CA1940: Autonomous vehicle planning and contro in uncertain environments
MERL is seeking a highly motivated and qualified intern to collaborate with the Control for Autonomy team in research on planning and control for autonomous vehicles in uncertain surrounding environments. The research domain includes algorithms for path planning and control in environments that are uncertain and perceived by sensing and predicted according to models and data. The ideal candidate is expected to be working towards a PhD with strong emphasis in vehicle guidance and control, and to have interest and background in as many as possible of: vehicle dynamics modeling and control, sensor uncertainty modeling, data-driven prediction, predictive control for uncertain systems, motion planning. Good programming skills in MATLAB, Python are required, knowledge of C/C++, rapid prototyping systems, automatic code generation, vehicle simulation packages (CarSim, CarMaker) or ROS are a plus. The expected start of of the internship is in the late Spring/Early Summer 2022, for a duration of 3-6 months.
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ST2083: Deep Learning for Radar Perception
The Computation Sensing team at MERL is seeking a highly motivated intern to conduct fundamental research in radar perception. Expertise in deep learning-based object detection, multiple object tracking, data association, and representation learning (detection points, heatmaps, and raw radar waveforms) is required. Previous hands-on experience on open indoor/outdoor radar datasets is a plus. Familiarity with the concept of FMCW, MIMO, and range-Doppler-angle spectrum is an asset. The intern will collaborate with a small group of MERL researchers to develop novel algorithms, design experiments with MERL in-house testbed, and prepare results for patents and publication. The expected duration of the internship is 3 months with a flexible start date.
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Recent Publications
- "Lunar Landing with Feasible Divert using Controllable Sets", AIAA SciTech, DOI: 10.2514/6.2024-0324, January 2024, pp. AIAA 2024-0324.BibTeX TR2024-004 PDF
- @inproceedings{Srinivas2024jan,
- author = {Srinivas, Neeraj and Vinod, Abraham P. and Di Cairano, Stefano and Weiss, Avishai},
- title = {Lunar Landing with Feasible Divert using Controllable Sets},
- booktitle = {AIAA SCITECH 2024 Forum},
- year = 2024,
- pages = {AIAA 2024--0324},
- month = jan,
- doi = {10.2514/6.2024-0324},
- url = {https://www.merl.com/publications/TR2024-004}
- }
, - "Perception-Aware Model Predictive Control for Constrained Control in Unknown Environments", Automatica, DOI: 10.1016/j.automatica.2023.111418, December 2023.BibTeX TR2023-147 PDF
- @article{Bonzanini2023dec,
- author = {Bonzanini, Angelo Domenico and Mesbah, Ali and Di Cairano, Stefano},
- title = {Perception-Aware Model Predictive Control for Constrained Control in Unknown Environments},
- journal = {Automatica},
- year = 2023,
- month = dec,
- doi = {10.1016/j.automatica.2023.111418},
- url = {https://www.merl.com/publications/TR2023-147}
- }
, - "Dual Parametric and State Estimation for Partial Differential Equations", IEEE Conference on Decision and Control, DOI: 10.1109/CDC49753.2023.10384246, December 2023, pp. 8156-8161.BibTeX TR2023-145 PDF
- @inproceedings{Mowlavi2023dec,
- author = {Mowlavi, Saviz and Benosman, Mouhacine},
- title = {Dual Parametric and State Estimation for Partial Differential Equations},
- booktitle = {IEEE Conference on Decision and Control (CDC)},
- year = 2023,
- pages = {8156--8161},
- month = dec,
- publisher = {IEEE},
- doi = {10.1109/CDC49753.2023.10384246},
- issn = {2576-2370},
- isbn = {979-8-3503-0125-0},
- url = {https://www.merl.com/publications/TR2023-145}
- }
, - "Risk-Averse Model Uncertainty for Distributionally Robust Safe Reinforcement Learning", Advances in Neural Information Processing Systems (NeurIPS), A. Oh and T. Neumann and A. Globerson and K. Saenko and M. Hardt and S. Levine, Eds., December 2023, pp. 1659-1680.BibTeX TR2023-143 PDF
- @inproceedings{Queeney2023dec,
- author = {Queeney, James and Benosman, Mouhacine},
- title = {Risk-Averse Model Uncertainty for Distributionally Robust Safe Reinforcement Learning},
- booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
- year = 2023,
- editor = {A. Oh and T. Neumann and A. Globerson and K. Saenko and M. Hardt and S. Levine},
- pages = {1659--1680},
- month = dec,
- publisher = {Curran Associates, Inc.},
- url = {https://www.merl.com/publications/TR2023-143}
- }
, - "A System-Level Cooperative Multi-Agent GNSS Positioning Solution", IEEE Transactions on Control Systems Technology, DOI: 10.1109/TCST.2023.3307339, Vol. 32, No. 1, pp. 158-173, October 2023.BibTeX TR2023-135 PDF
- @article{Greiff2023oct,
- author = {Greiff, Marcus and Di Cairano, Stefano and Kim, Kyeong Jin and Berntorp, Karl},
- title = {A System-Level Cooperative Multi-Agent GNSS Positioning Solution},
- journal = {IEEE Transactions on Control Systems Technology},
- year = 2023,
- volume = 32,
- number = 1,
- pages = {158--173},
- month = oct,
- doi = {10.1109/TCST.2023.3307339},
- url = {https://www.merl.com/publications/TR2023-135}
- }
, - "Physics-Informed Neural ODE (PINODE): Embedding Physics into Models using Collocation Points", Nature Scientific Reports, October 2023.BibTeX TR2023-136 PDF
- @article{Sholokhov2023oct,
- author = {Sholokhov, Aleksei and Liu, Yuying and Mansour, Hassan and Nabi, Saleh},
- title = {Physics-Informed Neural ODE (PINODE): Embedding Physics into Models using Collocation Points},
- journal = {Nature Scientific Reports},
- year = 2023,
- month = oct,
- url = {https://www.merl.com/publications/TR2023-136}
- }
, - "High-Fidelity Simulation of Horizon-Based Optical Navigation with Open-Source Software", International Astronautical Congress (IAC), October 2023, pp. IAC-23,C1,5,9,x78805.BibTeX TR2023-128 PDF
- @inproceedings{Shimane2023oct,
- author = {Shimane, Yuri and Miraldo, Pedro and Berntorp, Karl and Greiff, Marcus and Elango, Purnanand and Weiss, Avishai},
- title = {High-Fidelity Simulation of Horizon-Based Optical Navigation with Open-Source Software},
- booktitle = {International Astronautical Congress (IAC)},
- year = 2023,
- pages = {IAC--23,C1,5,9,x78805},
- month = oct,
- url = {https://www.merl.com/publications/TR2023-128}
- }
, - "Tailored Presolve Techniques in Branch-and-Bound Method for Fast Mixed-Integer Optimal Control Applications", Optimal Control Applications and Methods, DOI: 10.1002/oca.3030, Vol. 44, No. 6, pp. 3139-3167, August 2023.BibTeX TR2023-110 PDF
- @article{Quirynen2023aug2,
- author = {Quirynen, Rien and Di Cairano, Stefano},
- title = {Tailored Presolve Techniques in Branch-and-Bound Method for Fast Mixed-Integer Optimal Control Applications},
- journal = {Optimal Control Applications and Methods},
- year = 2023,
- volume = 44,
- number = 6,
- pages = {3139--3167},
- month = aug,
- doi = {10.1002/oca.3030},
- url = {https://www.merl.com/publications/TR2023-110}
- }
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- "Lunar Landing with Feasible Divert using Controllable Sets", AIAA SciTech, DOI: 10.2514/6.2024-0324, January 2024, pp. AIAA 2024-0324.
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