Guannan Qu

Assistant Professor, Electrical and Computer Engineering

Area of Expertise

Computational Methods, Power Systems & Smart Grid, Sustainable Architecture

Bio

Guannan Qu has been an Assistant Professor at the Electrical and Computer Engineering Department of Carnegie Mellon University since September 2021. He received his B.S. degree in Electrical Engineering from Tsinghua University in Beijing, China in 2014, and his Ph.D. in Applied Mathematics from Harvard University in Cambridge, MA in 2019. He was a CMI and Resnick postdoctoral scholar in the Department of Computing and Mathematical Sciences at California Institute of Technology from 2019 to 2021. He is the recipient of NSF CAREER Award, Top 5 Papers Award at IEEE Transactions on Smart Grid, Caltech Simoudis Discovery Award, PIMCO Fellowship, Amazon AI4Science Fellowship, and IEEE SmartGridComm Best Student Paper Reward. His research interest lies in control, optimization, and machine/reinforcement learning with applications to power systems, multi-agent systems, smart city, etc.

Education

• PhD., Applied Mathematics, Harvard University 
• B.S., Electrical Engineering, Tsinghua University

Research

Research of Prof. Qu involves developing machine learning and artificial intelligence methods for large-scale engineering systems, particularly energy systems like power grid. Highlights of Prof. Qu's research involves reinforcement learning for power systems, which has recently been recognized as the top 5 papers in IEEE Transactions on Smart Grid within the past 3 years (2023).