Zhenge Jia (贾振格)
10:00-11:00 a.m., September 22, 2023, GMT+8
Room 1801, Science Building #1 (Yanyuan)
The rise in chronic diseases, combined with an aging population and a healthcare professional shortage, has driven the extensive use of mobile and implantable devices for effective management of diverse health conditions. Recent years have seen burgeoning interest in exploiting the rapid advancements in artificial intelligence (AI) to augment these devices' performance. This development leads to improved patient outcomes, reduced healthcare costs, and enhanced patient autonomy. However, due to individual differences, an one-for-all AI model cannot always provide the best performance and personalized AI is demanded to tailor the model for each individual. In addition, compounded by the privacy, security, and safety constraints, model personalization must often be done on the medical device with limited hardware resources. In this talk, I will first illustrate the resource sustainability issues in the development of AI/ML for health, and demonstrate our proposed on-device personalized AI techniques that can potentially transform the landspace of implantable devices. Additionally, I will introduce the world-first TinyML design contest for health organized at ICCAD 2022.
Zhenge Jia is currently a postdoctoral research associate in the Department of Computer Science and Engineering at the University of Notre Dame. He received his Ph.D. degree in Electrical and Computer Engineering at the University of Pittsburgh in 2022. He received his B.S. degree with honors in Engineering and Computer Science at Australian National University in 2017. His research interests include personalized deep learning and on-device AI for health. He published more than 10 papers in Nature Machine Intelligence, DAC, ICCAD, TCAD and received the Second Place Award in Ph.D. forum at DAC 2023. He has served on the technical program committee of ICCAD and severed as the reviewer for TCAD, TNNLS, Nature Scientific Reports, JETC, TCPS, ESL, TCAS-II, etc.
School of Computer Science