Guannan Qu
Assistant Professor
Department of Electrical and Computer Engineering
Carnegie Mellon University
Contact: gqu [at]
Office: Porter B22

I am an assistant professor at the Department of Electrical and Computer Engineering at Carnegie Mellon University. From 2019 to 2021, I was a CMI and Resnick postdoc in the CMS Department of California Institute of Technology, working with Prof. Steven Low and Prof. Adam Wierman. I obtained my Ph.D. degree from Harvard SEAS working with Prof. Na Li in 2019. I obtained my B.S. degree from Tsinghua University in Beijing, China in 2014.

I am broadly interested in control, optimization, and machine learning. Particularly, I strive to develop theories that make machine learning applicable in real-world large scale engineering systems. My research is interdisciplinary in nature that develops new mathematical tools in machine/reinforcement learning, control theory, optimization, network science and applies these tools to cyber physical systems, power systems, transportation systems, robotics and beyond, with provable performance and resilience guarantee. For more details, please see the research page.

My CV can be found here (updated in Feb 2023).

I am expected to recurit 1-2 students in the Fall 2023 admision cycle. If you are interested in working with me, feel free to reach out!


  • December 2022: Our paper ``Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning’’ (link) has been accepted to SIGMETRICS 2023!
  • November 2022: Our paper ``Near-optimal distributed linear-quadratic regulator for networked systems (link)’’ has been accepted to SIAM Journal on Control and Optimization.
  • October 2022: two new members joined my group. Welcome, Alex and Ziyi!
  • September 2022: two new papers accepted to NeurIPS 2022
    • On the sample complexity of stabilizing LTI systems on a single trajectory (link)
    • Bounded-regret MPC via perturbation analysis: prediction error, constraints, and nonlinearity (link)
  • May 2022: one new paper in ICML 2022: Decentralized Online Convex Optimization in Networked Systems (link)
  • October 2021: Our paper on scalable multi-agent RL for networked systems (link) has been accepted to Operations Research!
  • September 2021: I am starting at CMU as an assistant professor!