Advancing Efficient and Trustworthy AI on the Edge - Jiangwei Sun
- Starts: 10:00 am on Tuesday, January 28, 2025
- Ends: 11:00 am on Tuesday, January 28, 2025
Title: Advancing Efficient and Trustworthy AI on the Edge; Abstract: Edge AI brings intelligence closer to users, enabling real-time, personalized interactions while maintaining data privacy. However, the increasing reliance on edge devices presents two significant challenges: ensuring efficient AI operations within resource-constrained environments and addressing trustworthiness concerns to safeguard sensitive on-device data. In this talk, Jiangwei Sun will first talk about efficient model training and personalization on edge devices, focusing on methods that eliminate the need for backpropagation to reduce computational and memory costs. Then, Jiangwei will present works on enhancing privacy and robustness for Edge AI, introducing strategies to protect data integrity and defend against adversarial threats. These efforts address critical limitations and pave the way for efficient and trustworthy Edge AI solutions. Bio: Jingwei Sun is a final-year Ph.D. student in ECE at Duke University, advised by Prof. Yiran Chen. Jingwei Sun’s research focuses on efficient and trustworthy edge intelligent systems. His work appears in AI conferences such as NeurIPS, ICML, CVPR, and ICCV , as well as system conferences such as MobiCom, SenSys, and MLsys. He has received the Best Paper Award from the AAAI Spring Series Symposium 2024. See https://jingwei-sun.com/
- Location:
- CDS 1646