Caiwen Ding

Caiwen Ding is an Assistant Professor at the School of Computing, University of Connecticut. His research focuses on algorithm-system co-design of machine learning/artificial intelligence, computer architecture, privacy-preserving machine learning, and neuromorphic computing. He actively explores computer vision, natural language processing, and machine learning applications in electronic design automation (EDA).

• Education: Ph.D., Northeastern University (Boston), 2019

Research Trends: His work bridges machine learning with hardware optimization (FPGAs/GPUs) and addresses cross-disciplinary challenges in secure computation and AI-driven EDA tools. Collaborative efforts span computer architecture, heterogeneous computing, and cognitive modeling for neural systems.

Scientific Awards & Honors

• NSF CAREER Award
• Amazon Research Award
• CISCO Research Award
• Best Paper Award at AAAI DCAA 2023
• Outstanding student paper award at HPEC 2023
• Best Paper Award Nomination at DATE 2018 and DATE 2021
• Publicity paper at DAC 2022
• Stanford’s World’s Top 2% Scientists (2023)
• UConn Research Excellence Awards (2021, 2023)
• UConn Provost’s Excellent in Teaching Award (2021)

Contact: caiwen.ding@uconn.edu | Phone: (860) 486-0006