Yiran Chen

Professor in the Department of Electrical and Computer Engineering

Yiran Chen received B.S. (1998) and M.S. (2001) from Tsinghua University and Ph.D. (2005) from Purdue University. After five years in the industry, he joined the University of Pittsburgh in 2010 as Assistant Professor and was promoted to Associate Professor with tenure in 2014, holding Bicentennial Alumni Faculty Fellow. He is now the John Cocke Distinguished Professor of Electrical and Computer Engineering at Duke University and serving as the director of the NSF AI Institute for Edge Computing Leveraging the Next-generation Networks (Athena), the NSF Industry-University Cooperative Research Center (IUCRC) for Alternative Sustainable and Intelligent Computing (ASIC), and the co-director of Duke Center for Computational Evolutionary Intelligence (DCEI). His group focuses on the research of new memory and storage systems, machine learning and neuromorphic computing, and mobile computing systems. Dr. Chen has published 1 book and about 600 technical publications and has been granted 96 US patents. He has served as the associate editor of more than a dozen international academic periodicals and served on the technical and organization committees of about 70 international conferences. He is now serving as the Editor-in-Chief of the IEEE Circuits and Systems Magazine. He received 9 best paper awards, 1 best poster award, and 15 best paper nominations from international conferences and workshops. He received numerous awards for his technical contributions and professional services such as the IEEE CASS Charles A. Desoer Technical Achievement Award, the IEEE Computer Society Edward J. McCluskey Technical Achievement Award, etc. He has been the distinguished lecturer of IEEE CEDA and CAS. He is a Fellow of the AAAS, ACM, and IEEE, and now serves as the chair of ACM SIGDA.

Appointments and Affiliations

  • Professor in the Department of Electrical and Computer Engineering
  • Professor of Computer Science

Contact Information


  • Ph.D. Purdue University, 2005

Research Interests

Emerging memory and storage technologies

Embedded systems, CPS, edge computing, and mobile applications

Neuromorphic computing, deep learning and system security

Low power circuit and system

Awards, Honors, and Distinctions

  • Charles A. Desoer Technical Achievement Award. Institute of Electrical and Electronics Engineers (IEEE), Circuits and Systems Society. 2023
  • Distinguished Lecturer. IEEE Circuits and Systems Society. 2023
  • Stansell Family Distinguished Research Award. Pratt School of Engineering, Duke University. 2022
  • Edward J. McCluskey Technical Achievement Award. Institute of Electrical and Electronics Engineers (IEEE), Computer Society. 2022
  • AAAS Fellow. American Association for the Advancement of Science. 2022
  • Clarivate Highly Cited Researchers. Clarivate. 2021
  • Outstanding Electrical and Computer Engineer (OECE) Award. Purdue’s School of Electrical and Computer Engineering. 2021
  • ACM Fellow. Association for Computing Machinery. 2020
  • HPCA Hall of Fame. IEEE Computer Society, Technical Committee on Computer Architecture. 2020
  • Distinguished Lecturer. IEEE Council on Electronic Design Automation. 2018
  • IEEE Fellow. Institute of Electrical and Electronics Engineers. 2018
  • Outstanding New Faculty Award . ACM’s Special Interest Group on Design Automation (SIGDA). 2014
  • National Science Foundation CAREER Awards - Multiple Sciences. National Science Foundation (NSF). 2013

Courses Taught

  • COMPSCI 393: Research Independent Study
  • ECE 590: Advanced Topics in Electrical and Computer Engineering
  • ECE 661: Computer Engineering Machine Learning and Deep Neural Nets
  • ECE 891: Internship
  • ECE 899: Special Readings in Electrical Engineering

In the News

Representative Publications

  • Zhang, T., D. Cheng, Y. He, Z. Chen, X. Dai, L. Xiong, F. Yan, H. Li, Y. Chen, and W. Wen. “NASRec: Weight Sharing Neural Architecture Search for Recommender Systems.” In Acm Web Conference 2023  Proceedings of the World Wide Web Conference, Www 2023, 1199–1207, 2023. https://doi.org/10.1145/3543507.3583446.
  • Hanson, E., M. Horton, H. H. Li, and Y. Chen. “DefT: Boosting Scalability of Deformable Convolution Operations on GPUs.” In International Conference on Architectural Support for Programming Languages and Operating Systems  Asplos, 3:134–46, 2023. https://doi.org/10.1145/3582016.3582017.
  • Hanson, E., S. Li, X. Qian, H. H. Li, and Y. Chen. “DyNNamic: Dynamically Reshaping, High Data-Reuse Accelerator for Compact DNNs.” Ieee Transactions on Computers 72, no. 3 (March 1, 2023): 880–92. https://doi.org/10.1109/TC.2022.3184272.
  • Lyu, Bo, Shiping Wen, Yin Yang, Xiaojun Chang, Junwei Sun, Yiran Chen, and Tingwen Huang. “Designing Efficient Bit-Level Sparsity-Tolerant Memristive Networks.” Ieee Transactions on Neural Networks and Learning Systems PP (March 2023). https://doi.org/10.1109/tnnls.2023.3250437.
  • Pang, Meng, Binghui Wang, Mang Ye, Yiu-Ming Cheung, Yiran Chen, and Bihan Wen. “DisP+V: A Unified Framework for Disentangling Prototype and Variation From Single Sample per Person.” Ieee Transactions on Neural Networks and Learning Systems 34, no. 2 (February 2023): 867–81. https://doi.org/10.1109/tnnls.2021.3103194.