Who’s Pi-Cheng Hsiu
January 1st, 2022
Embedded Software and Intermittent Computing
Dr. Pi-Cheng Hsiu received the Ph.D. degree in computer science and information engineering from National Taiwan University in 2009. He is currently a Research Fellow (Professor) and the Deputy Director of the Research Center for Information Technology Innovation (CITI), where he leads the Embedded and Mobile Computing Laboratory, and is also a Joint Research Fellow with the Institute of Information Science, Academia Sinica, Taiwan, a Jointly Appointed Professor with the Department of Computer Science and Engineering, National Chi Nan University, and a Jointly Appointed Professor with the College of Electrical Engineering and Computer Science, National Taiwan University. He was a Visiting Scholar with the Department of Computer Science, University of Illinois at Urbana-Champaign, in 2007 and with the Department of Electrical and Computer Engineering, University of Pittsburgh, in 2019.
Dr. Hsiu constantly publishes papers at the premier venues in embedded systems, real-time systems, and design automation. His works were respectively nominated for the Best Paper Awards at IEEE/ACM CODES+ISSS 2019, 2020, and 2021, of which the last two received the Best Paper Awards in a row. He is a recipient of the 2019 Young Scholars’ Creativity Award of the Foundation for the Advancement of Outstanding Scholarship, the 2019 Exploration Research Award of the Pan Wen Yuan Foundation, and the 2015 Scientific Paper Award of the Y. Z. Hsu Science and Technology Memorial Foundation. He serves as an Associate Editor of the ACM Transactions on Cyber-Physical Systems, Track Co-Chairs of IEEE/ACM ISLPED and ACM SAC, and in the Technical Program Committees of major conferences in his field, including RTSS, RTAS, CODES+ISSS and DAC.
Dr. Hsiu’s research goal is to realize Intermittent Artificial of Things (iAIoT), enabling battery-less IoT devices to intermittently execute deep neural networks (DNN) via ambient power. iAIoT is a novel research direction at the intersection of intermittent computing and deep learning, and once realized, would create innovative applications.
He has led a research team to release a suite of system runtime and libraries, facilitating AI and IoT application developers to easily build low cost, intermittent-aware inference systems. In particular, an intermittent operating system (TCAD’20), which was the first attempt to allow multitasking and task concurrency on intermittent systems, makes complicated intermittent applications increasingly possible. The HAWAII middleware (TCAD’20), which comprises an inference engine and API library, enables hardware accelerated intermittent DNN inference. In addition, the iNAS framework (TECS’21) was the first framework that introduces intermittent execution behavior into neural architecture search to automatically find intermittently-executable DNN models. HAWAII and iNAS received the Best Paper Awards, respectively, for two years in a row at IEEE/ACM CODES+ISSS 2020 and 2021. Such recognition indicates the innovativeness of his research and contributions to the community.