Kai-Chiang Wu received his Ph.D. degree in electrical and computer engineering from Carnegie Mellon University (CMU), Pittsburgh, PA, in 2011. From 2011 to 2013, he was with Intel Corporation, Hillsboro, OR, USA, as a senior software engineer working on the research and development of CAD tools for reliability verification. He is currently an associate professor in the Department of Computer Science, National Yang Ming Chiao Tung University (NYCU), Taiwan. His research interests include AI computing platform design, approximate computing for AI applications, computer-aided design (CAD) for reliability, fault tolerance and error resilience.
More recently, Dr. Wu has expanded thespectrum of his research interests to cover (i) AI for design & design automation (D & DA) and (ii) D & DA for AI. The topics and projects of his research can be synergistically integrated to build an AI computing platform.A concrete example of building an AI computing platform is: applyingneural architecture search(NAS) to find the optimal neural network architecture given a task (e.g., image classification) running on a specific hardware platform (e.g., Google Edge TPU on Raspberry Pi).
Dr. Wu’s research team won the 3rd place in On-device Visual Intelligence Competition (OVIC), part of 2020 Low-Power Computer Vision Challenge (LPCVC). In 2018, he was a recipients of Semiconductor Award for Young Researcher (from Taiwan Semiconductor Industry Association). Dr. Wu’s work published at IEEE VLSI Test Symposium (VTS 2017) was nominated for Best Paper Award; he was the recipient of a Best Paper Award from IEEE International Conference on Computer Design (ICCD 2008).