Lei Deng received his B.E. degree and Ph.D. degree from University of Science and Technology of China, Hefei, China, and Tsinghua University, Beijing, China, in 2012 and 2017, respectively. He was a Postdoctoral Fellow working with Professor Yuan Xie at Scalable Energy-Efficient Architecture Lab (SEAL), Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA, USA from 2017-2021. He is currently an Assistant Professor at Center for Brain Inspired Computing Research (CBICR), Tsinghua University, Beijing, China. His research interests span the area of brain-inspired computing, machine learning, and computer architecture.

Dr. Deng has been involved in professional services such as serving as a Guest Associate Editor for Frontiers in Neuroscience (section Neuromorphic Engineering) and Frontiers in Computational Neuroscience, and a PC member for International Joint Conference on Neural Networks (IJCNN) 2021, IEEE International Conference on Application-Specific Systems, Architectures and Processors (ASAP) 2021, and International Symposium on Neural Networks (ISNN) 2019. He was a recepient of MIT Technology Review Innovators Under 35 China 2019. He serves as a reviewer for a number of journals such as IEEE Transactions on Neural Networks and Learning Systems (TNNLS), Neural Networks, IEEE Transactions on Computers, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), IEEE Transactions on Biomedical Circuits and Systems (TBioCAS), IEEE Transactions on Cybernetics (TCYB), IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI), IEEE Transactions on Cognitive and Developmental Systems (TCDS), ACM Transactions on Design Automation of Electronic Systems (TODAES), ACM Transactions on Embedded Computing Systems (TECS), Frontiers in Neuroscience (section Neuromorphic Engineering), IEEE Access, Electronics, Sensors, Journal of Imaging, and conferences such as Advances in Neural Information Processing Systems (NeurIPS), International Conference on Learning Representations (ICLR), Conference on Computer Vision and Pattern Recognition (CVPR), International Conference on Computer Vision (ICCV), IEEE International Symposium on High-Performance Computer Architecture (HPCA), IEEE International Symposium on Circuits and Systems (ISCAS), IEEE Symposium Series on Computational Intelligence (SSCI), IEEE Conference on Industrial Electronics and Applications (ICIEA), etc.




Tsinghua University (THU) 2012-2017, Center for Brain Inspired Computing Research, Research Domains: Neuromorphic Chip, Machine Learning, Non-Volatile Memory, Complex Networks


University of Science and Technology of China (USTC) 2008-2012, Department of Precision Machinery and Precision Instrument, Research Domains: Robotics, Photoelectrics



Wu Wenjun AI Outstanding Youth Award of CAAI (2021), Young Scholar of Chinese Institute for Brain Research, Beijing (2021), MIT Technology Review Innovators Under 35 China (2019), Ph.D. Graduate ‘Zijing’ Scholar of THU (top-10, 2017), Academic Rising Star of Department of Precision Instrument of THU (2017), Best Oral Award in the 1st PhD Forum of Beijing Innovation Center for Future Chip (2017), First Prize of Comprehensive Scholarship of THU (2016), THU (China)-NSK (Japan) Friendship Best Paper Award (2016), Graduate Best Paper Award of Department of Precision Instrument of THU (2015), Graduate National Scholarship of China (2015), Best Oral Award in the “THU-CAEP” Ph.D. Student Summer Intern Defense (2015), Outstanding Ph.D. Student Summer Intern of THU (2015), Graduate Social Work Award of THU (2015), THU “12.9” Counselor Award (2015), Outstanding Student Cadres of THU (2014), Outstanding Student Cadres of Graduate Union of THU (2013)


Second Place of USTC Robot Competition (2010), Undergraduate National Encouragement Scholarship of China (2010)

Research Summary

My research interests include Brain-inspired Computing, Machine Learning, Computer Architecture, etc.

Research Projects:

ASIC Chip for Artificial and/or Spiking Neural Networks

Hybrid Neural Networks

Spiking Neural Network Learning and Applications

Domain-Specific Computing Architecture