Author

Dr. Caiwen Ding is an assistant professor in the Department of Computer Science and Engineering at the University of Connecticut (UConn). He received his Ph.D. degree from Northeastern University, Boston in 2019, supervised by Prof. Yanzhi Wang. His research interests mainly include efficient machine learning system, privacy preserving machine learning. His work has been published in high-impact venues (e.g., DAC, ICCAD, ASPLOS, ISCA, MICRO, HPCA, SC, FPGA, Oakland, CCS, MLSys, CVPR, IJCAI, AAAI, ACL, ICML, EMNLP, ICRA, DATE, IEEE TCAD, IEEE TPDS). He has received the best paper nomination at DATE 2018 and DATE 2021, best paper award at the DL-Hardware Co-Design for AI Acceleration (DCAA) workshop at AAAI 2023, publicity paper at DAC 2022, and the 2021 Excellent in Teaching Award from UConn Provost. His team won first place in accuracy and fourth place overall at the 2022 TinyML Design Contest at ICCAD. His research has been funded by NSF, DOE, USDA, SRC, and multiple industry sponsors such as Travelers, Eversource.