Nuwan Jayasena
Nuwan Jayasena is a Fellow at AMD Research, and leads a team exploring hardware support, software enablement, and application adaptation for processing in memory. His broader interests include memory system architecture, accelerator-based computing, and machine learning. Nuwan holds an M.S. and a Ph.D. in Electrical Engineering from Stanford University and a B.S. from the University of Southern California. He is an inventor of over 70 US patents, an author of over 30 peer-reviewed publications, and a Senior Member of the IEEE. Prior to AMD, Nuwan was a processor architect at Nvidia Corp. and at Stream Processors, Inc.
Mike Howard
Mike has over 15 years of experience tracking the DRAM and memory markets. Prior to TechInsights, he built the DRAM research service at Yole. Prior to Yole, Mike spent time at IHS covering DRAM and Micron Technology where he had roles in engineering, marketing, and corporate development. Mike holds an MBA from The Ohio State University and a BS in Chemical Engineering and BA in Finance from the University of Washington.
Puja Das
Dr. Puja Das, leads the Personalization team at Warner Brothers Discovery (WBD) which includes offerings on Max, HBO, Discovery+ and many more.
Prior to WBD, she led a team of Applied ML researchers at Apple, who focused on building large scale recommendation systems to serve personalized content on the App Store, Arcade and Apple Books. Her areas of expertise include user modeling, content modeling, recommendation systems, multi-task learning, sequential learning and online convex optimization. She also led the Ads prediction team at Twitter (now X), where she focused on relevance modeling to improve App Ads personalization and monetization across all of Twitter surfaces.
She obtained her Ph.D from University of Minnesota in Machine Learning, where the focus of her dissertation was online learning algorithms, which work on streaming data. Her dissertation was the recipient of the prestigious IBM Ph D. Fellowship Award.
She is active in the research community and part of the program committee at ML and recommendation system conferences. Shas mentored several undergrad and grad students and participated in various round table discussions through Grace Hopper Conference, Women in Machine Learning Program colocated with NeurIPS, AAAI and Computing Research Association- Women’s chapter.