Professor Kelly Shaw: Kelly Shaw is a Professor of Computer Science at Williams College. Prior to joining Williams College, she was a faculty member at the University of Richmond and Reed College. She earned an undergraduate degree in computer science from Duke University and earned a Master’s degree and a Ph.D. in computer science from Stanford University. Shaw's research focuses on parallel architectures. Her work has explored the design and use of memory systems in chip multiprocessors and graphics processors, as well as testing and verification of the correctness of parallel systems, including IoT platforms. Shaw is passionate about supporting a diverse computing community and engaging undergraduate students in research. She currently serves as chair of WICARCH and as co-chair of the Computing Research Association’s Education committee. She has been an organizer and speaker for workshops and conferences supporting diversity in computing, including the Grace Hopper Celebration of Women in Computing and CRA-WP Career Mentoring, Grad Cohort, and Discipline Specific Workshops. Additionally, she was a member of the first Cultural Competence in Computing Fellows program.
Dr. Alan Bivens: Dr. Alan Bivens is currently the Director of Data Services, IBM Public Cloud, leading a variety of Cloud Data technologies including Cloud Databases, Object Storage, and Kafka offerings. Alan comes to this role after holding numerous senior management roles in IBM Research and Executive Staff positions in IBM’s Blockchain business unit. Alan is also a prolific writer with over 50 filed patents (earning him the distinction of being an IBM Master Inventor), and over 40 publications in the areas of cloud and distributed systems, systems management, and machine learning technologies.
Dr. Valentina Salapura: Dr. Valentina Salapura is a Senior Fellow at AMD Research. Previously, she was a System Architect at the IBM T.J. Watson Research Center, and a faculty member at the Technische Universität Wien. Valentina is a computer architect for large computer systems, from supercomputers to cloud computing data centers. Valentina is a prolific inventor and holds more than 400 US patents, and she published a number of papers and several book chapters on processor and network architecture. Valentina was named Fellow of the Institute of Electrical and Electronics Engineers (IEEE) in 2012 for contributions to the architecture and design of multiprocessor systems, and is a recipient of the 2006 ACM Gordon Bell Prize for Special Achievements.
Mentoring Table Hosts:
Professor Reetuparna Das: Reetu Das is an Associate Professor at the University of Michigan. Prior to this, she was a research scientist at Intel Labs, and the researcher-in-residence for the Center for Future Architectures Research. She received her Ph.D. in Computer Science and Engineering from Pennsylvania StateUniversity, University Park. Some of her recent projects include in-memory architectures, custom computing for precision health and AI, fine-grain heterogeneous core architectures for mobile systems, and low-power scalable interconnects for kilo-core processors. She has authored over 45 papers, filed 7 patents, served on over 30 technical program committees, and served as program co-chair for MICRO-52. She has received two IEEE Top Picks awards, an NSF CAREER award, CRA-W's Borg Early Career Award, Intel Outstanding Researcher Award, and Sloan Foundation Fellowship. Prof. Das has been inducted into IEEE/ACM MICRO and ISCA Hall of Fame.
Dr. Amir Yazdanbakhsh: Dr. Amir Yazdanbakhsh joined Google Research as a Research Scientist in 2019, following a one year AI residency. He is the co-founder and co-lead of the Machine Learning for Computer Architecture team. The team leverage the recent machine learning methods and advancements to innovate and design better hardware accelerators. The work of the team has been covered by media outlets including WIRED, ZDNet, AnalyticsInsight, InfoQ. He is also interested in designing large-scale distributed systems for training machine learning applications. To that end, he led the development of a massively large-scale distributed reinforcement learning system that scales to TPU Pod and efficiently manages thousands of actors to solve complex, real-world tasks. As a case study, his team demonstrates how using this highly scalable system enables reinforcement learning to accomplish chip placement in an hour instead of days or weeks by human effort. Amir received his Ph.D. degree in computer science from the Georgia Institute of Technology. His Ph.D. work has been recognized by various awards, including Microsoft PhD Fellowship and Qualcomm Innovation Fellowship.
Mahesh Madhav: Mahesh Madhav works at Ampere Computing as a CPU Performance Architect and a Media Producer. He spent 16 years in the Intel Architecture team, modeling performance, verifying RTL, and optimizing workloads. Currently he leads the core performance effort for the Ampere core product line, and serves on the SPEC-CPU benchmark selection committee. He is a hiring manager at Ampere and a DEI champion. Listen to his podcast, Amplified by Ampere to gain insights into what kind of jobs exist for engineers in the semiconductor industry and the technical culture that fosters solving problems in a psychologically safe working environment.
CASA: The Computer Architecture Student Association (CASA) is an independent student-run organization with the express purpose of developing and fostering a positive and inviting student community within computer architecture. Created by students for students, CASA aims to support the student community throughout the demanding years of academic study.
Professor Elba Garza: Elba Garza is an entering Assistant Teaching Professor at the University of Washington in Seattle. Her PhD work focused on improving prediction techniques for front end structures. She now helps introduce students to computer science via the introductory teaching sequence at UW, and helps steer them to computer architecture by teaching their computer organization offering. She helped co-found the Computer Architecture Student Association (or CASA) in 2020 as a means to help create a community for students in the computer architecture research area.
Dr. Abdulrahman Mahmoud: Abdulrahman is a postdoc researcher in computer science at Harvard University, working with Dr. David Brooks and Dr. Gu-Yeon Wei. His research interests are broadly in the areas of computer architecture, machine learning, reliability, and approximate computing. His work focuses on addressing the role hardware errors play on an application’s error tolerance, by designed tools and techniques to help understand how hardware errors propagate and affect software.
Abdulrahman completed his PhD at UIUC under the guidance of Dr. Sarita Adve in the RSim Research Group. During his graduate studies, he was very fortunate to be the recipient of the Mavis Future Faculty Fellowship, to be invited to the 7th Heidelberg Laureate Forum, and to recieve multiple awards for teaching and mentoring undergraduate students. Prior to joining UIUC, Abdulrahman completed his BSE from Princeton University, where he was the recipient of the John Ogden Bigelow Jr. Prize in Electrical Engineering. He helped co-found the Computer Architecture Student Association (CASA).
Dr. Shuwen Deng: Shuwen Deng is now a postdoctoral research fellow at University of Michigan, working with Professor Baris Kasikci. She will join Tsinghua University as an assistant professor in 2023. She received Ph.D. from Yale University, advised by Professor Jakub Szefer. Her research bridges computer architecture and security.
Dr. Gokul Ravi: Gokul Ravi is a CIFellows postdoc at the University of Chicago working with Prof. Fred Chong. His research targets building a hybrid computing ecosystem for practical quantum advantage. He received his PhD from UW-Madison in 2020 and was awarded the Harold A. Peterson Best ECE Dissertation Award and recognized as a 2019 Rising Star in Computer Architecture.
Abenezer Wudenhe: Abenezer Wudenhe is a PhD student at University of California Riverside (UCR), majoring in Computer Science. He has received an undergraduate degree in Computer Engineering from the University of Maryland, Baltimore County (UMBC). Areas of interest include domain specific applications acceleration through the use of memory and accelerators. Personal hobbies include reading, movies, and spending time with friends.
Puolami Das: Poulami Das is a Ph.D. Candidate at Georgia Institute of Technology advised by Prof. Moin Qureshi. Her research focuses on developing compiler optimizations and software techniques to improve the fidelity of near-term quantum applications as well as designing architecture and system-level solutions for enabling fault-tolerant quantum computing in the future. Poulami obtained her Master’s degree from The University of Texas, Austin and Bachelor’s degree from National Institute of Technology (NIT), Durgapur. She is the recipient of the Microsoft Research PhD Fellowship, Institute Gold Medals at NIT Durgapur, and has been selected as a Rising Star in EECS. Her research has been recognized with the Best Research Award at the Design Automation Conference Ph.D. Forum, Cleaver Award for the most outstanding Ph.D. dissertation proposal in Electrical and Computer Engineering, Georgia Tech, Best Paper Award at Computing Frontiers, and has appeared in top architecture and systems venues like MICRO, HPCA, and ASPLOS.
Phaedra Curlin: Phaedra Curlin is a 1st year Electrical Engineering PhD student working under Dr. Tamara Lehman at the University of Colorado Boulder, where she also obtained her BSc in Electrical and Computer Engineering. Her interests lie in computer architecture and security. Her current research involves developing open-source ASIC implementations of the Advanced Encryption Standard and evaluating the different design trade-offs between them.