Organizers

Yingyan (Celine) Lin is currently an Associate Professor in the School of Computer Science at Georgia Institute of Technology. She leads the Efficient and Intelligent Computing (EIC) Lab, which focuses on developing efficient machine learning systems via cross-layer innovations from algorithm to architecture down to chip design, aiming to promote green AI and enable ubiquitous machine learning powered intelligence. She received a Ph.D. degree in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign in 2017.

Prof. Lin is an NSF CAREER Award, IBM Faculty Award, and Facebook Faculty Research Award recipient, and recently received the ACM SIGDA Outstanding Young Faculty Award. She was selected as a Rising Star in EECS by the 2017 Academic Career Workshop for Women at Stanford University. She received a Best Student Paper Award at the 2016 IEEE International Workshop on Signal Processing Systems (SiPS 2016), and the 2016 Robert T. Chien Memorial Award for Excellence in Research at UIUC. Prof. Lin is currently the lead PI on multiple multi-university projects (e.g., RTML and 3DML) and her group has been funded by NSF, NIH, DARPA, ONR, Qualcomm, Intel, HP, IBM, and Meta.

Yongan Zhang is a PhD student at Georgia Institute of Technology. He obtained his BS degree from Rice University in 2019. His research focuses on hardware acceleration for deep learning algorithms.

Yonggan Fu is a PhD student at Georgia Institute of Technology. He obtained his BS degree from University of Science and Technology of China in 2019 and his MS degree from Rice University in 2022. His research interest is efficient and robust machine learning.

Chaojian Li is a PhD student at Georgia Institute of Technology. He obtained his B.S. degree from Tsinghua University in 2019. His research focuses on deep learning on edge devices, NAS, and neural rendering.

Yang Zhao is a 5th year PhD student. She obtained her M.S. and B.S. degrees from Fudan University. Her research interest is interested in co-design for deep learning, computer architecture, and EDA. She is a recipient of the Cadence Women in Technology Scholarship in 2020, and was an intern of the ASIC & VLSI Research group in NVIDIA in the summer of 2022.