Leadership

Peter Baldwin is the founder of Myrtle.ai, a company focused on hardware-software co-design for efficient machine learning inference and other core data-center workloads. Through Peter, Myrtle.ai was instrumental in setting up the speech transcription benchmark for MLPerf. Peter previously founded a software development company which wrote distributed data center software. He was also a Senior Technical Director at several multinational visual effects companies. Peter holds a PhD in Pure Mathematics from Cambridge University, UK.

Ritika Borkar is a Senior Deep Learning Architect at Nvidia focusing on HW and SW optimizations for High Performance AI Computing on GPUs and datacenter systems. Previously, she worked on microarchitecture definition, ASIC design, and verification for IPs at Atmel and Nvidia. Since MLPerf’s inception in 2018, Ritika has influenced rules and processes for the training suite of benchmarks. She holds a master’s degree in Electrical Engineering from the University of Minnesota, and a bachelor’s degree from the National Institute of Technology at Trichy in India.

Ramesh Chukka is a Deep Learning Manager at Intel with focus on performance analysis and benchmarking. He has 14+ years of experience leading benchmark development and working with industry benchmark consortiums. Ramesh received M.Tech from IIT Madras and B.E from Andhra University, India.

Sally Doherty is Chief Marketing Officer at AI company, Graphcore, where she leads the global marketing team responsible for go to market, growth, brand, marketing and communications. Previously, she led marketing for Icera, a cellular modem chip and product company, which was sold to Nvidia in 2011 for $435M and then worked in a range of marketing roles at Nvidia until joining Graphcore in 2016. Early in her career, Sally ran marketing and communications campaigns for a diverse range of technology companies including the launching Playstation for Sony Computer Entertainment. Sally holds an M.A. in English Literature from the University of Cambridge.

Debojyoti Dutta (Debo) currently leads AI solutions and engineering at Nutanix. Prior to this he led engineering for Nutanix’s cloud management portfolio, including AI driven operations and cost governance. Before Nutanix, Debo was a visiting scholar at Stanford (Management sciences and engineering), a founding member of MLCommons, and a Distinguished Engineer at Cisco. He obtained his postdoctoral training in computational biology and a PhD in computer science from the University of Southern California and a BTech in computer science and engineering from the Indian Institute of Technology, Kharagpur.

James Goel leads the AI/ML standards group at Qualcomm where he is a Director of Technical Standards. He is on the board of the Video Electronics Standards Association (VESA) and is the chair of the MIPI Alliance Technical Steering Group. Previously, he was the VP of Engineering at Silicon Optix before it was acquired by Qualcomm in 2011. He holds a Bachelor’s of Applied Science (B.A.Sc) in Electrical Engineering from the University of Waterloo in Canada and is a licensed Professional Engineer (P. Eng.) in Ontario where he’s practiced for the last 31 years.

Vijay Janapa Reddi is an Associate Professor at Harvard University. Before joining Harvard, he was an Associate Professor at The University of Texas at Austin in the Department of Electrical and Computer Engineering. His research interests include computer architecture and runtime systems, specifically in the context of autonomous machines and mobile and edge computing systems. Dr. Janapa Reddi has received multiple honors and awards, including the National Academy of Engineering (NAE) Gilbreth Lecturer Honor and has been inducted into the MICRO and HPCA Halls of Fame. He received a Ph.D. in computer science from Harvard University, M.S. from the University of Colorado at Boulder and B.S from Santa Clara University.

David Kanter is a Founder, Board Member, and the Head of MLPerf for MLCommons where he helps lead the MLPerf benchmarks. He has 16+ years of experience in semiconductors, computing, and machine learning. He founded a microprocessor and compiler startup, was an early employee at Aster Data Systems, and has consulted for industry leaders such as Intel, Nvidia, KLA, Applied Materials, Qualcomm, Microsoft and many others. David holds a Bachelor of Science degree with honors in Mathematics with a specialization in Computer Science, and a Bachelor of Arts with honors in Economics from the University of Chicago.

Jon Khazam is a senior executive, board member, advisor, and investor with over 30 years of technology leadership experience and 18 years of private and public company board experience. Jon was most recently EVP Strategy and Business Development at Graphcore, a leading startup enabling the next generation of machine intelligence. Prior to joining Graphcore, Jon held a number of roles spanning microprocessors, graphics, and software at Intel Corporation. Jon has served on the boards of multiple companies, including Integrated Silicon Solution, Inc., the Eclipse Foundation, and Zend Technologies. Jon has a MBA from the Haas School of Business at U.C. Berkeley and a B.S.E.E. from Cornell University.

Peter Mattson is a senior staff engineer at Google. He founded and is President of MLCommons, and founded and was General Chair of the MLPerf consortium that preceded it. Previously, he founded the Programming Systems and Applications Group at Nvidia Research, was VP of software infrastructure for Stream Processors Inc (SPI), and was a managing engineer at Reservoir Labs. His research focuses on understanding machine learning models and data through quantitative metrics and analysis. Peter holds a PhD and MS from Stanford University and a BS from the University of Washington.

Yanni leads an organization at Microsoft in Windows+Devices focused on 3D Graphics and AI workloads on Windows. His passion is working on stream compute problems in both client and cloud. Yanni has worked at Microsoft for over six years. He has also worked at industry-leading companies such as Apple, Intel, Google, AMD, and Bloomberg. Yanni works with multiple startups, such as InterviewKickstart, to help engineers grow across all disciplines. He completed his master’s and bachelor’s degrees at Boston University.

Rebecca Weiss is the Executive Director of MLCommons. She is a distinguished data scientist and computational social scientist known for innovative large-scale data analysis of online behavior. Previously, she was the head of Research and Innovation at Mozilla, where she created the privacy-preserving Rally user data donation platform, and also founded and led the Firefox Data Science organization. Weiss serves on the board of the Pew Research Center, has been a fellow at Princeton, Harvard, and Columbia, and an advisor to U.S. Congress on AI policy and strategy. She holds a PhD from Stanford University, an MS from the Massachusetts Institute of Technology, and a BA with class 1 honours from the University of British Columbia.

Carole-Jean Wu is a Research Scientist at Facebook AI Research. Her research focus lies in the domain of computer system architecture with particular emphasis on energy- and memory-efficient systems. Her recent research has pivoted into designing systems for machine learning execution at-scale and tackling system challenges to enable efficient, responsible AI execution. Carole-Jean chairs the MLPerf Recommendation Benchmark Advisory Board and co-chaired MLPerf Inference. She is the recipient of the NSF CAREER Award, Facebook AI Infrastructure Mentorship Award, the IEEE Young Engineer of the Year Award, the Science Foundation Arizona Bisgrove Early Career Scholarship, and the Intel PhD Fellowship, among a number of Best Paper awards. Carole-Jean holds tenure from ASU and received her M.A. and Ph.D. from Princeton and B.Sc. from Cornell.

Weiming Zhao is a Senior Staff Engineer and Architect at Alibaba, where he leads the development and optimizations for AI systems and compilers on. He is also responsible for enabling various AI HW/SW systems, from edge to cloud. He is the main contributor of Alibaba’s heterogeneous AI software — HALO/ODLA, the software platform submitted to MLPerf v2.1 Inference. Previously, he worked for Qualcomm focusing on compiler optimizations for mobile processors. Weiming earned a PhD of Computer Science degree from the Michigan Technological University.