Welcome! I'm an Assistant Professor in the ECE Department at the University of California, San Diego. Broadly speaking, my research interests span the analysis and design of adaptive, robust, and high-performance feedback-based dynamic mechanisms for control, optimization, estimation, and learning, with an emphasis on hybrid dynamical systems. Our laboratory works on the development of foundational theories and algorithms for the safe and efficient deployment of feedback-enabled autonomous machines in different engineering, societal, and biological systems. To achieve this overarching goal, our research combines tools from control theory, dynamical systems, optimization, game theory, and network science. Application domains include cyber-physical systems (power systems, connected autonomous vehicles, transportation systems), robotic systems, and biotechnology.
Prospective Students, Postdocs, and Visitors
We are always looking for highly motivated students, researchers, and visiting scholars with a strong mathematical background and interest in control, optimization, and learning systems. If interested, please reach out at poveda@ucsd.edu For more information about admissions to UCSD please click this link.
News and Highlights
09/2023: Our paper "Momentum-Based Nash Set-Seeking over Networks via Multi-Time Scale Hybrid Inclusions" was accepted in IEEE Transactions on Automatic Control.
07/2023: Our paper "Averaging Theory for a Class of Stochastic Hybrid Dynamical Systems with Oscillating Vector Fields" was accepted at the 2023 IEEE Conference on Decision and Control.
07/2023: New project with NREL on Hybrid Control of Power Grids.
06/2023: New project with Sandia National Laboratories on Game-Theoretic Control of Power Grids.
06/2023: Joined the Editorial Board (as Associate Editor) of the journal IEEE Control Systems Letters (LCSS).
06/2023: Big congrats to Mahmoud Abdelgalil for receiving the Best Student Paper award at the 2023 American Control Conference!
06/2023: Honored to receive the 2023 Donald P. Eckman Award from the American Automatic Control Council.
05/2023: Co-organized a workshop at the 2023 American Control Conference on recent advances of Model-Free Equilibrium Seeking Control.
03/2023: New NSF project on Fixed-Time Equilibrium-Seeking Control.
03/2023: Two papers accepted at the 2023 IFAC World Congress.
02/2023: Our paper "Control Systems for Low-Inertia Power Grids: A Survey on Virtual Power Plants" appeared in the journal IEEE Access.
02/2023: Our paper "High-Order Decentralized Pricing Dynamics for Congestion Games: Harnessing Coordination to Achieve Acceleration", was accepted for publication at the 2023 American Control Conference.
02/2023: Joined the Editorial Board (as Associate Editor) of IFAC journal Nonlinear Analysis: Hybrid Systems (NAHS).
01/2023: New project with Sandia National Laboratory on coordinated control systems for virtual power plants.
01/2023: Joined the IEEE Technical Committee on Hybrid Systems.
12/2022: Our paper "A Stochastic Binary Vertex-Triggering Resetting Algorithm for Global Synchronization of Pulse-Coupled Oscillators" was accepted in IEEE Transactions on Control of Network Systems.
12/2022: Selected as Excellent Reviewer for the AIAA Journal of Guidance, Control, and Dynamics.
10/2022: Invited talk at Allerton Conference on stochastic hybrid decision-making algorithms.
07/2022: Two papers accepted at the 61st IEEE Conference on Decision and Control.
07/2022: Our paper "Online Optimization of Switched LTI Systems Using Continuous-Time and Hybrid Accelerated Gradient Flows" was accepted in Automatica.
07/2022: Our paper "High-Performance Optimal Incentive Seeking for Transactive Control of Traffic Congestion" was accepted in the European Journal of Control.
07/2022: Joined the Conference Editorial Board (as Associate Editor) of IEEE CSS.
07/2022: Joined the ECE department at UC San Diego.
04/2022: Daniel Ochoa (Ph.D. student) was selected to participate in the 2022 CPS Rising Stars Workshop.
03/2022: Our paper "Accelerated Continuous-Time Approximate Dynamic Programming via Data-Assisted Hybrid Control" was accepted in the 14th IFAC International Workshop on Adaptive and Learning Control Systems.
03/2022: Our paper "Novel Use of Online Optimization in a Mathematical Model of COVID-19 to Guide the Relaxation of Pandemic Mitigation Measures" was accepted in Nature Scientific Reports.
03/2022: Our paper "Sliding-Seeking Control: Model-Free Optimization with Hard Constraints" was accepted in the Learning for Dynamics and Control Conference (L4DC).
02/2022: Two papers accepted in the American Control Conference.
02/2022: Received NSF Early Career (CAREER) award.
12/2021: Our IEEE CDC paper "Safe Model-Free Optimal Voltage Control via Continuous-Time Zeroth-Order Methods" won the Outstanding Student Paper Award and was a finalist for the Best Student Paper Award.
11/2021: Selected as a 2022 RIO Faculty Fellow at CU Boulder.
11/2021: Received AFOSR Young Investigator Program award.
08/2021: Our paper "Time-Varying Optimization of LTI Systems via Projected Primal-Dual Gradient Flows" was accepted in IEEE Transactions on Control of Network Systems.
07/2021: Three papers accepted in the 60th IEEE Conference on Decision and Control.
05/2021: Our paper "Scalable Resetting Algorithms for Synchronization of Pulse-Coupled Oscillators over Rooted Directed Graphs" was accepted in Automatica.
04/2021: Received the 2020 CCDC Best Ph.D. Thesis Award from UC Santa Barbara.
04/2021: Short press release published here.
04/2021: Our work "Computation-Aware Distributed Optimization over Networks: A Hybrid Dynamical Systems Approach" was presented at the 2021 CPS IoT Week workshop on Computation-Aware Algorithmic Design for Cyber-Physical Systems .
03/2021: Received RIO Seed Grant on Control, Game Theory, and Multi-Vehicle Systems. Co-PIs: Xudong Chen and Eric Frew.
03/2021: Our paper "Accelerated Concurrent Learning Algorithms via Data-Driven Hybrid Dynamics and Non-smooth ODEs" was accepted in the 2021 Learning For Dynamics and Control (L4DC) Conference.
02/2021: Patent granted on Robust Source Seeking and Formation Learning-based Controllers.
02/2021: Our paper "Non-Smooth Extremum Seeking Control with User-Prescribed Fixed-Time Convergence" was accepted in IEEE Transactions on Automatic Control.
01/2021: Our paper "Coordinated Hybrid Source Seeking with Robust Obstacle Avoidance in Multi-vehicle Autonomous Systems" was accepted in IEEE Transactions on Automatic Control.
01/2021: Two papers accepted at the 2021 American Control Conference.
12/2020: Our paper titled "Extremum Seeking Under Persistent Gradient Deception: A Switching Systems Approach" was accepted in IEEE Control Systems Letters.
12/2020: Our paper titled "Excitation Conditions for Uniform Exponential Stability of the Cooperative Gradient Algorithm over Weakly Connected Digraphs" was accepted in IEEE Control Systems Letters.
11/2020: AB Nexus Research Collaboration Grant awarded. PI: E. Dall'Anese, Co-PIs: A. Buchwald, and JIP.
11/2020: Presented our work Distributed Accelerated Optimization Algorithms with Distributed Restarting at the 2020 NeurIPS Workshop (LXAI).
10/2020: Joined the IFAC Technical Committee in Adaptive and Learning Systems.
09/2020: Our paper "Robust Hybrid Zero-Order Optimization Algorithms with Acceleration via Averaging in Time" was accepted in Automatica.
09/2020: Our paper "Data-Enabled Extremum Seeking: A Cooperative Concurrent Learning-Based Approach", was accepted for in International Journal of Adaptive Control and Signal Processing.
06/2020: Two papers accepted in the 2020 IEEE Conference on Decision and Control.
05/2020: Our paper "Robust Optimization over Networks Using Distributed Restarting of Accelerated Dynamics" was accepted for publication in IEEE Control Systems Letters.
04/2020: Our survey paper on learning-based multi-agent hybrid systems was one of the most downloaded papers of 2019 in International Journal of Adaptive Control and Signal Processing.
02/2020: Received NSF Research Initiation Initiative (CRII) award.
02/2020: Our paper "A Newton-Like Extremum Seeking Controller with Practical Fixed-Time Convergence" was accepted in the 2020 IFAC World Congress.
01/2020: 2 papers have been accepted at the 2020 American Control Conference!
01/2020: I will be teach in the 2020-Spring Semester the research-based course ECEN 5018 Hybrid Dynamical Systems: Theory and Applications. Check the syllabus here.
08/2019: Received ASIRT grant "Coopetitive Mobile Energy Network Systems: Achieving Robust Decentralized Autonomy via Data-Driven Intelligent Algorithms and Interacting Architectures". Co-Pi's: E. Dall'Anese, D. Maksimovic, and L. Pao.
08/2019: I will teach in the Fall Semester the research-based course ECEN 5008 Adaptive Control and Reinforcement Learning.
07/2019: 5 papers accepted in the 58th IEEE Conference on Decision and Control.
07/2019: Attended the NSF-cosponsored workshop on Control for Networked Transportation Systems (CNTS), in Philadelphia, PA.
05/2019: 2 papers accepted in the 11th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2019).
01/2019: I will be teaching in the 2019-Spring Semester the research-based course ECEN 5018 Hybrid Dynamical Systems: Theory and Applications.
02/2019: New paper published in International Journal of Adaptive Control and Signal Processing. A survey on learning-based multi-agent hybrid systems.
01/2019: New paper published in Automatica on hybrid mechanisms for robust synchronization and coordination of multi-agent networked sampled-data systems.
01/2019: Joined the ECEE Department of the University of Colorado Boulder as an Assistant Professor.