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 mechanisms for control, optimization, estimation, and learning, with an emphasis on hybrid and nonsmooth dynamical systems. Our Decision-Making and Nonlinear Control Laboratory seeks to develop foundational theories and algorithms for the safe deployment of autonomous systems in different engineering, societal, and biological systems. Our research combines tools from robust nonlinear/hybrid control theory, optimization, game theory, and network science. Application domains include energy systems, connected autonomous vehicles, transportation systems, mobile robots, and biology.

Prospective Students/Postdocs/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. If interested, please reach out at poveda@ucsd.edu For more information about admissions to UCSD please click this link.

News and Highlights

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 ECE department at UC San Diego.

04/2022: Daniel Ochoa (Ph.D. student) was selected to participate in the 2022 CPS Rising Stars Workshop.

04/2022: Our paper "Fixed-Time Nash Equilibrium Seeking in Time-Varying Networks" was accepted in IEEE Transactions on Automatic Control.

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 grant NSF CAREER award.

01/2022: Our paper "Online Optimization of LTI Systems Under Persistent Attacks: Stability, Tracking, and Robustness" was accepted in Nonlinear Analysis: Hybrid Systems.

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 grant Young Investigator Program Award by AFOSR.

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 grant Research Initiation Initiative Award (CRII).

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.