Na (Lina) Li 黎娜

Na (Lina) Li

I am a Winokur Family Professor of Electrical Engineering and Applied Mathematics in the School of Engineering and Applied Sciences (SEAS) at Harvard University. I am also serving as the area chair for Electrical Engineering. I am a Scientific Advisor of Singularity Energy, Inc, a startup providing a suite of innovative products, developer APIs, and intelligent tools for companies to build the future of decarbonization solutions, and Elastro Inc, a neurotechnology startup developing next-generation brain-computer interfaces to transform the diagnosis and treatment of neurological and psychiatric disorders

My research lies in control, learning, and optimization of dynamical systems, including theory development, algorithm design, and applications to real-world cyber-physical systems, such as robotics, bio-medical systems, energy systems, buildings, bio-medical systems, etc. The goal is to develop foundational learning and control tools to explore and exploit real-world system structures that can lead to reliable, efficient, and autonomous operation of these systems. My work is highly interdisciplinary, integrating mathematical, computational, engineering, economic, and biological tools.

My current research focuses on the interplay between control and learning—such as model-based and model-free reinforcement learning, offline and online learning, diffusion models, scalable multiagent-learning, etc—and their applications to robotics, neuroscience, and emerging directions in agentic and physical AI for science and engineering. I am actively seeking students and postdocs with strong backgrounds in these areas to join my group.

I have received IFAC Thoma Medal, McDonald Mentoring Award, Donald P. Eckman Award, ONR YIP Award, AFOSR YIP Award, NSF CAREER Award, Harvard Climate Change Solution Fund, Harvard PSE Accelerator Award, along with other awards. 

For my research publications, please check my Google scholar page.

Lina_CVMay2025.pdf

Latest News

  • Dec 2025: We are organizing a NeurIPS workshop on UrbanAI: Harnessing Artificial Intelligence for Smart Cities. Submissions on related topics are welcome!
  • Nov 2025: I was elected to IEEE Fellow, effective 1 January 2026. Thank you to all of my mentors, collaborators, and students for all the years of support!
  • July 2025: Shahriar Talebi  joined UCLA as an assistant professor. Congratulations!
  • July 2025: Runyu Zhang joined MIT as a postdoc fellow. Congratulations!   
  • Jan 2025: We are organizing an NSF workshop on Reinforcement Learning at Harvard SEAS. You are welcome to check the details on the website.
  • Dec 2024: I am honored to receive Antonio Ruberti Young Researcher Prize awarded by IEEE Control and System Society. The prize recognizes outstanding achievement in research in systems and control by a young researcher who is 40 years old or younger.
  • July 2024: Slides of my keynote talk at L4DC on representation-based control and learning have been posted here. Some of my other recent presentation slides have also been posted on this webpage.
  • March 2024: Our paper, Deep Learning-Based Model Predictive Control for Automatic Window Operations in Winter, won a 2024 Best Paper Award by ASHRAE (the American Society of Heating, Refrigerating and Air-Conditioning Engineers).
  • Dec 2023: Our paper, Reinforcement learning for selective key applications in power systems: Recent advances and future challenges, was selected as one of the Top 5 papers in IEEE Transactions on Smart Grid in the past 3 years.
  • Fall 2023: Our former Ph.D. student, Dr. Xin Chen, has started his tenure-track assistant professor position at Texas A&M. Congratulations, Xin!
  • Fall 2023: Our former Ph.D. student, Dr. Yingying Li, has started her tenure-track assistant professor position at UIUC. Congratulations, Yingying!
  • 07/2023: Starting July 1st, I will be appointed as Winokur Family Professor of Electrical Engineering and Applied Mathematics.
  • 04/2023: Dr. Xin Chen won the Best Research Award (one of two, out of over 100 participants) with the Grid Edge Grand Prize of $5,000 in the Ph.D. Dissertation Challenge in IEEE PES Grid Edge Technologies Conference and Exposition 2023.
  • 03/2023: Dr. Xin Chen's Ph.D. thesis, Distributed Data-Driven Decision-Making for Smart Sustainable Power Systems, was selected as one of the four outstanding doctoral dissertations (2020-2022) by IEEE PES PEEC. Xin will present his thesis at a two-hour panel session at the IEEE PES General Meeting 2023. Congratulations, Xin Chen!
  • 08/2022: I am honored to receive IFAC Manfred Thoma Medal, which recognizes the outstanding contributions of a young researcher and/or engineer under the age of 40 to the field of systems and control in its widest sense.

Office Hours

By appointments

For Prospective Students

I am always looking for highly-motivated students with a strong mathematical background and interests in theory and computation. Students who are interested in working with large-scale systems-- in particular, large-scale optimization and control for networked systems are encouraged to apply. Application information can be found here. Apologies for not being able to answer your inquiry emails about the application. 

For Prospective Postdocs

If you're interested in pursuing a postdoc position, please reach out to me directly through email.