Research Areas: Efficient machine learning through cross-layer innovations
Yingyan (Celine) Lin is currently an Associate Professor in the School of Computer Science at the 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 a Facebook Research Award (2020), NSF CAREER Award (2021), IBM Faculty Award (2021), and Meta Faculty Research Award (2022) recipient, and received the ACM SIGDA Outstanding Young Faculty Award in 2022. She was selected as a Rising Star in EECS by the 2017 Academic Career Workshop for Women at Stanford University. She received the 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 of multiple multi-university projects, such as RTML and 3DML, and her group has been funded by NSF, NIH, DARPA, SRC, ONR, Qualcomm, Intel, HP, IBM, and Meta. Her group’s research won first place in both the University Demonstration at DAC 2022 and the ACM/IEEE TinyML Design Contest at ICCAD 2022, and was selected as an IEEE Micro Top Pick of 2023.