Shiqi Zhao received the B.S. degree in applied physics from Xi’an Polytechnic University, Xi’an, China, in 2016, and the M.S. degree in integrated circuits and intelligent systems from Peking University, Beijing, China, in 2019. He joined the Center of Excellence in Biomedical Research on Advanced Integrated-on-chips Neurotechnologies (CenBRAIN Neurotech), School of Engineering, Westlake University, Hangzhou, China in 2019, where he is currently pursuing his Ph.D. degree.
Shiqi Zhao is particularly interested in deep learning algorithm, digital circuit design. He is now following his passion to do research on low-precision neural network for biomedical applications and deep neural network hardware or neuromorphic hardware digital circuit design. His project aims to build a hardware based on software and hardware co-design for biomedical processing.
 Zhao S, Yang J, Sawan M. Energy-efficient neural network for epileptic seizure prediction. IEEE Transactions on Biomedical Engineering, 2021.
 Zhao S, Yang J, Xu Y, et al. Binary Single-Dimensional Convolutional Neural Network for Seizure Prediction, IEEE International Symposium on Circuits and Systems (ISCAS), 2020.