Hi, I’m Jeffrey.
I am a Ph.D. Candidate in the Systems Control Group at University of Toronto, where I also received my B.A.Sc. (with Honours) and M.A.Sc. in 2020 and 2022, respectively. My thesis is in data-driven control theory; specifically, I am working under the guidance of Prof. John Simpson-Porco to develop low-gain controllers to solve the disturbance rejection problem in unknown linear time-invariant systems using frequency response and input-output data.
I am proud to be a recipient of the NSERC PGS-D, OGS, QEII-GSST, Hatch Graduate Scholarship for Sustainable Energy Research, and H. W. Price Research Fellowship in Electrical Engineering during my graduate studies.
Previously, I worked on the AC power flow problem from 2019 to 2022. I worked with Prof. Zeb Tate to develop convolutional neural networks to accelerate the Newton-Raphson power flow computations in my undergrad, and I later developed a more rigorous fixed-point algorithm to solve the AC power flow problem. In addition to my research work, I am also actively exploring and learning about topics in deep reinforcement learning, operations research, renewable energy market and quantitative finance.
Thank you for visiting my website, and please get in touch at liangjie dot chen at mail dot utoronto dot ca if you have any questions or would like a chat!