Daniel Ochoa

Orcid: 0000-0002-5442-1105

Affiliations:
  • University of California San Diego, Department of Electrical and Computer Engineering, CA, USA
  • University of Colorado, Department of Electrical, Computer and Energy Engineering, Boulder, CO, USA (former)


According to our database1, Daniel Ochoa authored at least 15 papers between 2019 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
Robust global optimization on smooth compact manifolds via hybrid gradient-free dynamics.
Autom., 2025

2024
Momentum-Based Nash Set-Seeking Over Networks via Multitime Scale Hybrid Dynamic Inclusions.
IEEE Trans. Autom. Control., July, 2024

Decentralized concurrent learning with coordinated momentum and restart.
Syst. Control. Lett., 2024

Prescribed-time stability in switching systems with resets: A hybrid dynamical systems approach.
Syst. Control. Lett., 2024

2023
Multi-time scale control and optimization via averaging and singular perturbation theory: From ODEs to hybrid dynamical systems.
Annu. Rev. Control., January, 2023

Control Systems for Low-Inertia Power Grids: A Survey on Virtual Power Plants.
IEEE Access, 2023

High-Order Decentralized Pricing Dynamics for Congestion Games: Harnessing Coordination to Achieve Acceleration.
Proceedings of the American Control Conference, 2023

2022
High-performance optimal incentive-seeking in transactive control for traffic congestion.
Eur. J. Control, 2022

Accelerated Continuous-Time Approximate Dynamic Programming via Data-Assisted Hybrid Control.
CoRR, 2022

2021
Robust Optimization Over Networks Using Distributed Restarting of Accelerated Dynamics.
IEEE Control. Syst. Lett., 2021

Accelerated Concurrent Learning Algorithms via Data-Driven Hybrid Dynamics and Nonsmooth ODEs.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Computation-aware distributed optimization over networks: a hybrid dynamical systems approach.
Proceedings of the CAADCPS '21: Proceedings of the Workshop on Computation-Aware Algorithmic Design for Cyber-Physical Systems, 2021

2020
A Multi-Critic Reinforcement Learning Method: An Application to Multi-Tank Water Systems.
IEEE Access, 2020

2019
Hybrid Robust Optimal Resource Allocation with Momentum.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Control of Urban Drainage Systems: Optimal Flow Control and Deep Learning in Action.
Proceedings of the 2019 American Control Conference, 2019


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