Research

My general research interests are centered around optimization, control, and learning in complex, cyber-physical and network systems. I seek to develop foundational theories, methods, and algorithms that enable the deployment of efficient, safe, and autonomous decision-making architectures to address engineering and societal challenges.

Theories, methods, and algorithms are primarily motivated by (and applied to) modern power systems. In addition to power systems, my research group aims to make impactful contributions in the broad area of cyber-physical and network systems. A distinctive aspect of my research lies in its robust connections between foundational theory and practical applications: our research pipeline initiates with a rigorous synthesis and analysis of decision-making architectures and extends to experiments and field demonstrations, aiming to maximize the impact and the technology transfer.

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Topics of current interest include:

  • Data-driven optimization and control of physical and dynamical systems.

  • Online optimization with system and human in-the-loop.

  • Safe online optimization of dynamical systems.

Theories and methods are motivated and applied to:

  • Modern power and energy systems.

  • Electrified transportation.

  • Autonomous and robotic systems.

Current funded projects

Online Optimization-Based Feedback Controllers for Dynamical Systems in Stochastic Environments with Partially Known Performance Metrics and Safety Constraints

  • Funded by the Air Force Office of Scientific Research, Dynamical Systems and Control Theory Program 

  • Principal Investigator: Jorge Cortes (University of California San Diego); co-PI: Emiliano Dall'Anese

  • Period of performance: 2023 - 2026.

 

Hybrid System Models and Algorithms for Resilient Transmission Systems

  • Funded by the U.S. Department of Energy, Advanced Grid Modeling Program 

  • Principal Investigator: Guido Cavraro (NREL); co-PIs: Jorge Poveda (University of California San Diego), Emiliano Dall'Anese

  • Period of performance: 2023 - 2025.

 

Closed-loop Optimization and Control of Physical Networks Subject to Dynamic Costs, Constraints, and Disturbances

  • Funded by the National Science Foundation, CMMI DCDS program.  

  • Principal Investigator. Co-PI: Jorge Cortes (University of California San Diego) 

  • Period of performance: 2021 - 2024.

 

NSF CAREER: Synthesis of Feedback-based Online Algorithms for Power Grids

  • Funded by the National Science Foundation, Energy, Power, Control, and Networks (EPCN) program.  

  • Principal Investigator

  • Period of performance: February 2020 - January 2025.

Past projects 

NSF ERC: Advancing Sustainability through Powered Infrastructure for Roadway Electrification 

  • NSF Engineering Research Center. Lead: Utah State University; team members: University of Colorado Boulder, Purdue University, University of Texas El Paso

  • Period of performance: 2020 - 2025.

 

NSF AMPS: Online and Model-free Optimization of Power and Energy Systems

  • Funded by the National Science Foundation, Division of Mathematical Sciences (DMS), Algorithms for Modern Power Systems (AMPS) program.  

  • Principal Investigator: Stephen Becker (University of Colorado Boulder). Co-PI: Emiliano Dall'Anese

  • Period of performance: 2019 - 2023.

 

Multi-objective Deep Reinforcement Learning for Grid-Interactive Energy-Efficient Buildings.

  • Funded by the U.S. Department of Energy (DOE), Buildings Technology Office 

  • Principal Investigator: Andrey Bernstein (NREL). Co-PIs: Emiliano Dall'Anese, Gregor Henze (University of Colorado Boulder)

  • Period of performance: 2019 - 2023.​

 

Control-theoretic design of data-driven policies for containing transmission of infectious diseases 

  • Funded by the AB Nexus seed grant.  

  • Principal Investigator. Co-PIs: Andrea Buchwald (University of Colorado Anschutz), Jorge I. Poveda (University of Colorado Boulder) 

  • Period of performance: 2020 - 2021.

 

Synthesis of Real-time Optimization Algorithms for Autonomous Urban Mobility

  • Funded by the National Renewable Energy Laboratory

  • Principal Investigator

  • Period of performance: 2020 - 2020.​

 

Design and Analysis of Online Algorithms for Next-generation Energy Systems

  • Funded by the National Renewable Energy Laboratory

  • Principal Investigator

  • Period of performance: 2018 - 2019.

 

Research Support for Autonomous Energy Systems Program

  • Funded by the National Renewable Energy Laboratory

  • Principal Investigator

  • Period of performance: 2018 - 2020.

 

Learning to Control Safety-Critical Systems: Providing Formal Correctness Guarantees for Learning-based Control of Safety-critical Systems.

  • Funded by the Research & Innovation Office of the University of Colorado Boulder.

  • Principal Investigator: Ashutosh Trivedi (University of Colorado Boulder). Co-PIs: Emiliano Dall'Anese, Fabio Somenzi (University of Colorado Boulder)

  • Period of performance: 2019 - 2020.

 

Real-time optimization and control of next-generation distribution infrastructure

  • U.S. Department of Energy (DOE), Advance Research Project Agency - Energy (ARPA-e), Network Optimized Distributed Energy Systems (NODES) program. 

  • Principal Investigator. Co-PIs: Steven Low (Caltech), Na Li (Harvard University), Sairaj Dhople (University of Minnesota), and Christopher Clarke (Southern California Edison). 

  • Period of performance: 2016 - 2019.