Feng Chen Ph.D.
Professor and Deputy Director of the Department of Automation, Tsinghua University
Deputy Dean of the Institute of Artificial Intelligence, Tsinghua University
Professor Chen primarily focuses on Brain-inspired Computing, Video and Image Processing, and Probability Graphical Models.
Tsinghua University, Ph. D., 2000
St. Petersburg State Polytechnic University, M.S., 1996
St. Petersburg State Polytechnic University, B.S. 1994
Tsinghua University, Professor, 2011 – current; Associate Professor, 2003.12 - 2011.12; Assistant Professor, 2000.04 - 2003.12
Carnegie Mellon University, Visiting Scholar, 2009.02 - 2009.09
Shangqi Guo, Zhaofei Yu, Fei Deng, Xiaolin Hu, and Feng Chen. Hierarchical Bayesian Inference and Learning in Spiking Neural Networks. IEEE Transactions on Cybernetics, 2019, PP(99):1
Zhaofei Yu, Feng Chen, and Fei Deng. Unification of MAP Estimation and Marginal Inference in Recurrent Neural Networks. IEEE Transactions on Neural Networks and Learning Systems, 2018, PP(99):1-6.
Liheng Bian, Jinli Suo, Qionghai Dai, Feng Chen. Experimental comparison of single-pixel imaging algorithms. Journal of the Optical Society of America A, 2018, 35(1): 78-87.
Fei Deng, Jianwu Dong, Xiangyu Wang, Ying Fang, Yu Liu, Zhaofei Yu, Jing Liu, and Feng Chen. Design and Implementation of a Noncontact Sleep Monitoring System Using Infrared Cameras and Motion Sensor. IEEE Transactions on Instrumentation and Measurement, 2018, 67(7): 1555-1563.
Liheng Bian, Jinli Suo, Feng Chen, Qionghai Dai. High-resolution multispectral imaging using a photodiode[C]//High-Speed Biomedical Imaging and Spectroscopy III: Toward Big Data Instrumentation and Management. International Society for Optics and Photonics, 2018, 10505: 1050507.
Dongqin Cai, Yin Yue, Xin Su, Miaomiao Liu, Yiwei Wang, Ling You, Fenghua Xie, Fei Deng, Feng Chen. Distinct Anatomical Connectivity Patterns Differentiate Subdivisions of the Nonlemniscal Auditory Thalamus in Mice. Cerebral cortex (New York, NY: 1991), 2018.
Zhaofei Yu, Feng Chen, Jianwu Dong. Neural Network Implementation of Inference on Binary Markov Random Field with Probability Coding. Applied Mathematics and Computation. 2017, 301: 193-200.
Zhaofei Yu, David Kappel, Robert Legenstein, Sen Song, Feng Chen, and Wolfgang Maass. CaMKII activation supports reward-based neural network optimization through Hamiltonian sampling. 2016.
Office: Room 721, the Central Building, Tsinghua University, Haidian District, Beijing