2025
SiPhyR: An End-to-End Learning-Based Optimization Framework for Dynamic Grid Reconfiguration.
IEEE Trans. Smart Grid, March, 2025
2024
Geometry-aware PINNs for Turbulent Flow Prediction.
CoRR, 2024
Using Parametric PINNs for Predicting Internal and External Turbulent Flows.
CoRR, 2024
2023
Flocks, games, and cognition: A geometric approach.
Syst. Control. Lett., April, 2023
RANS-PINN based Simulation Surrogates for Predicting Turbulent Flows.
CoRR, 2023
Improving Gradient Computation for Differentiable Physics Simulation with Contacts.
Proceedings of the Learning for Dynamics and Control Conference, 2023
Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems.
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Proceedings of the American Control Conference, 2023
2022
A Neural ODE Interpretation of Transformer Layers.
CoRR, 2022
EMVLight: a Multi-agent Reinforcement Learning Framework for an Emergency Vehicle Decentralized Routing and Traffic Signal Control System.
CoRR, 2022
Demystifying the Data Need of ML-surrogates for CFD Simulations.
CoRR, 2022
Physics-informed neural networks for modeling rate- and temperature-dependent plasticity.
CoRR, 2022
Accelerated Algorithms for a Class of Optimization Problems with Constraints.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022
On Using Hamiltonian Monte Carlo Sampling for RL.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022
EMVLight: A Decentralized Reinforcement Learning Framework for Efficient Passage of Emergency Vehicles.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
A Decentralized Reinforcement Learning Framework for Efficient Passage of Emergency Vehicles.
CoRR, 2021
A Differentiable Contact Model to Extend Lagrangian and Hamiltonian Neural Networks for Modeling Hybrid Dynamics.
CoRR, 2021
Extending Lagrangian and Hamiltonian Neural Networks with Differentiable Contact Models.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Benchmarking Energy-Conserving Neural Networks for Learning Dynamics from Data.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021
2020
Cluster Synchronization of Diffusively Coupled Nonlinear Systems: A Contraction-Based Approach.
J. Nonlinear Sci., 2020
Hamiltonian Q-Learning: Leveraging Importance-sampling for Data Efficient RL.
CoRR, 2020
Frequency-compensated PINNs for Fluid-dynamic Design Problems.
CoRR, 2020
Dissipative SymODEN: Encoding Hamiltonian Dynamics with Dissipation and Control into Deep Learning.
CoRR, 2020
Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control.
Proceedings of the 8th International Conference on Learning Representations, 2020
2019
Beacon-referenced Pursuit for Collective Motions in Three Dimensions.
CoRR, 2019
A Conditional Generative Model for Predicting Material Microstructures from Processing Methods.
CoRR, 2019
2018
BeeNestABM: An open-source agent-based model of spatiotemporal distribution of bumblebees in nests.
J. Open Source Softw., 2018
Bistability and Resurgent Epidemics in Reinfection Models.
IEEE Control. Syst. Lett., 2018
Social decision-making driven by artistic explore-exploit tension.
CoRR, 2018
Collective motion under beacon-referenced cyclic pursuit.
Autom., 2018
Beacon-referenced Mutual Pursuit in Three Dimensions.
Proceedings of the 2018 Annual American Control Conference, 2018
Feedback Controlled Bifurcation of Evolutionary Dynamics with Generalized Fitness.
Proceedings of the 2018 Annual American Control Conference, 2018
2017
A graph-theoretic approach to multitasking.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
A Formal Approach to Modeling the Cost of Cognitive Control.
Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017
Multitasking Capability Versus Learning Efficiency in Neural Network Architectures.
Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017
Constant bearing pursuit on branching graphs.
Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017
2016
A Graph-Theoretic Approach to Multitasking.
CoRR, 2016
Controlled vs. Automatic Processing: A Graph-Theoretic Approach to the Analysis of Serial vs. Parallel Processing in Neural Network Architectures.
Proceedings of the 38th Annual Meeting of the Cognitive Science Society, 2016
Investigating group behavior in dance: an evolutionary dynamics approach.
Proceedings of the 2016 American Control Conference, 2016
Stability and pure shape equilibria for beacon-referenced cyclic pursuit.
Proceedings of the 2016 American Control Conference, 2016
Synchronization bound for networks of nonlinear oscillators.
Proceedings of the 54th Annual Allerton Conference on Communication, 2016
2015
Biomimetic algorithms for coordinated motion: Theory and implementation.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015
Station keeping through beacon-referenced cyclic pursuit.
Proceedings of the American Control Conference, 2015
2014
Control-theoretic data smoothing.
Proceedings of the 53rd IEEE Conference on Decision and Control, 2014
2012
Trajectory smoothing as a linear optimal control problem.
Proceedings of the 50th Annual Allerton Conference on Communication, 2012
2010
Stabilizing a Flexible Beam on a Cart: A Distributed Port-Hamiltonian Approach.
J. Nonlinear Sci., 2010