PI: Lei Yang
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Dr. LEI YANG is currently an Assistant Professor in the Department of Information Sciences and Technology at George Mason University. Before that, she was an Assistant Professor in the Department of Electrical and Computer Engineering at the University of New Mexico, USA. She received her Ph.D. degree and B.E. degree in 2019 and 2013, respectively, from Chongqing University, China. She was a Post-Doctoral Research Associate in the Department of Computer Science and Engineering at the University of Notre Dame. She has the experience as a research scholar at the University of California, Irvine and the University of Pittsburgh from 2017 to 2019.
Lei’s primary research interests lie in the joint area of Hardware/Software Co-Exploration for Neural Network Architectures, Embedded Systems, Hardware/Software Co-Exploration for Neural Architectures, Embedded Systems, and High-Performance Computing. She is passionate about d Systems, Hardware/Software Co-Exploration for Neural Architectures, Automated Machine Learning, and ystem-Level Design and Optimization for Applied Machine Learning.
She has authored and co-authored more than 50 research articles in refereed international conferences and premier journals, including DAC, CODES+ISSS, ASP-DAC, ICCD, HPCC, RTCSA, IEEE Transactions (TC, TPDS, TVLSI, TCAD), ACM Transactions (TECS), and FGCS. She has received IEEE Transactions on Computer-Aided Design (TCAD) for the 2021 Donald O. Pederson Best Paper Award and Best Paper Award in ICCD 2017, and five Best Paper Nominations in ASP-DAC 2020, CODES+ISSS 2019, DAC 2019, ASP-DAC 2019, and ASP-DAC 2016. She is the TPC member of numerous highly-impacting conferences, including DAC, ICCAD, ASAP, ISVLSI, ASP-DAC, SAC, SOCC, etc., and the reviewer of highly-ranked international journals, including TC, TCAD, JETC, TODAES, TETC, JSA, etc. She organized DAC 2021 Early Career Workshop, E2ML workshop at GLVLSI 2021, and ACM/SIGDA ASP-DAC SRF 2023, also served as the registration chair of ICCD 2021, the special session chair of DAC 2021, and the technical session chair of ASP-DAC 2021 and SOCC 2020.
During Ph.D., Dr. Yang focused on the optimization of Embedded Systems and Computing Architecture Design; in particular, optimization algorithms are developed for high-performance and low-power Network-on-Chip based Multiprocessor System-on-Chips, thermo-reliable many-core systems, and novel Nonvolatile Memory (NVM)-based architectures. She published more than 30 research articles in refereed international conferences and premier journals, including DAC, ASP-DAC, CODES+ISSS, ICCD, and over 10 IEEE/ACM Transactions papers. She received Best Paper Award in ICCD’17, and Best Paper Nomination in ASP-DAC’16 and ASP-DAC’19.
As a post-doctoral research associate at the University of Notre Dame, Dr. Yang focused on Automated Machine Learning and Hardware/Software Co-exploration for Neural Architectures. Her work is the first to propose the co-exploration framework of neural architecture and hardware design, which enables the automatic exploration of the best pair of neural architectures and accelerator designs. Continuous research is collaborated with researchers from Facebook and Georgia Institute of Technology. In recognition for this work, she received 2021 Donald O. Pederson TCAD Best Paper Award, Best Paper Nominations in DAC’19, CODES+ISSS’19 and ASP-DAC’20.
Ph.D. Students:
Daniel Manu, Fall 2020 ~ Now
Junhuan Yang, Fall 2021 ~ Now
Petro Mushidi Tshakwanda, Fall 2021 ~ Now (Co-advise with Michael Devetsikiotis)
Yi Sheng, Fall 2022 ~ Now (Co-advise with Dr. Weiwen Jiang)
Undergranduate Students:
Chaeeun Park, Fall 2020 ~ Fall 2021
Lucas Zhou, Fall 2020 ~ Spring 2021