EJ Kim is an Associate Professor in the Department of
Computer Science & Engineering, Texas A&M University, where she has been since 2003. She received the BS degree in computer science from the Korea
AdvancedInstitute of Science and Technology, Korea, in 1989, the MS degree in computer science from the Pohang University of Science and Technology, Korea, in
1994, and the PhD degree in computer science and engineering from the Pennsylvania
State University in 2003. Her research interests
include computer architecture, approximation computing, parallel/distributed systems, low-power design, secure computing, and performance evaluation.

I teach computer architecture and design courses at SJSU's computer engineering department. I have 13 years of academic work experience. My research interests includes processor architectures, memory subsystems, and performance evaluations.
I earned my M.Tech. (2011) and Ph.D. (2022) degrees from Amrita Vishwa Vidyapeetham in Bangalore, India, where I worked on low-power cache architecture and fine-grain data classification in cache coherence mechanisms to improve system performance. My work has appeared in computer architecture conferences (PDP) and the JPDC journal.

Natalie Enright Jerger is the Canada Research Chair in Computer Architecture and a Professor of Electrical and Computer Engineering at the University of Toronto. She is currently serving as the Director of the Division of Engineering Scinece at the University of Toronto. Prior to joining the University of Toronto, she received her MSEE and PhD from the University of Wisconsin-Madison in 2004 and 2008, respectively. She received her Bachelor's degree from Purdue University in 2002. She is a recipient of the Ontario Ministry of Research and Innovation Early Researcher Award in 2012, the 2014 Ontario Professional Engineers Young Engineer Medal recipient and the 2015 Borg Early Career Award winner. She served as the program co-chair of the 7th Network-on-Chip Symposium, as the program chair of the 20th International Symposium on High Performance Computer Architecture and as program co-chair for the International Conference on Architectural Support for Programming Languages and Operating Systems in 2023. She is currently serving as the ACM SIGARCH Chair. Her current research explores on-chip networks, approximate computing, IoT architectures and machine learning acceleration. She is also passionate about increasing the representation of women in computing, particular in computer architecture. She is the former chair of the organizing committee for the Women in Computer Architecture group (WICARCH). In 2017, she co-authored the second edition of the Computer Architecture Synthesis Lecture on On-Chip Networks with Li-Shiuan Peh and Tushar Krishna. Her research has been supported by NSERC, Intel, CFI, AMD and Qualcomm.

Lillie's general research interests are in specialized hardware and software-hardware co-design, and her current work focuses on enabling efficient deep learning. She received her B.A. in Physics and Computer Science from Colgate University in 2016, and she is currently pursuing her PhD in Computer Science at Harvard University, where she works with David Brooks and Gu-Yeon Wei.