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.
Sandeep Singh
Tom Sheffler
Tom earned his PhD from Carnegie Mellon in Computer Engineering with a focus on parallel computing architectures and prrogramming models. His interest in high-performance computing took him to NASA Ames, and then to Rambus where he worked on accelerated memory interfaces for providing high bandwidth. Following that, he co-founded the cloud video analytics company, Sensr.net, that applied scalable cloud computing to analyzing large streams of video data. He later joined Roche to work on next-generation sequencing and scalable genomics analysis platforms. Throughout his career, Tom has focused on the application of high performance computer systems to real world problems.
Uri Rosenberg
Uri Rosenberg is the Specialist Technical Manager of AI & ML services within enterprise support at Amazon Web Services (AWS) EMEA. Uri works to empower enterprise customers on all things ML: from underwater computer vision models that monitor fish to training models on satellite images in space; from optimizing costs to strategic discussions on deep learning and ethics. Uri brings his extensive experience to drive success of customers at all stages of ML adoption.
Before AWS, Uri led the ML projects at AT&T innovation center in Israel, working on deep learning models with extreme security and privacy constraints.
Uri is also an AWS certified Lead Machine learning subject matter expert and holds an MsC in Computer Science from Tel-Aviv Academic College, where his research focused on large scale deep learning models.
Helen Byrne
Helen leads the Solution Architects team at Graphcore, helping innovators build their AI solutions using Graphcore’s Intelligence Processing Units (IPUs). She has been at Graphcore for more than 5 years, previously leading AI Field Engineering and working in AI Research, working on problems in Distributed Machine Learning. Before landing in the technology industry, she worked in Investment Banking. Her background is in Mathematics and she has a MSc in Artificial Intelligence.
Jim Handy
Jim Handy of Objective Analysis has over 35 years in the electronics industry including 20 years as a leading semiconductor and SSD industry analyst. Early in his career he held marketing and design positions at leading semiconductor suppliers including Intel, National Semiconductor, and Infineon. A frequent presenter at trade shows, Mr. Handy is highly respected for his technical depth, accurate forecasts, widespread industry presence and volume of publication. He has written hundreds of market reports, articles for trade journals, and white papers, and is frequently interviewed and quoted in the electronics trade press and other media.
Sony Varghese
Dr. Sony Varghese is Senior Director of strategic marketing for memory in the Semiconductor Products Group at Applied Materials. In this role, he is involved in identifying challenges to scaling and future key inflections in the memory industry. Prior to Applied Materials, he worked on developing various memory technologies within the R&D organization at Micron Technologies. Dr. Varghese has over 25 U.S. patents issued or pending in the area of semiconductor processing and integration. He holds a Ph.D. in Mechanical and Materials Engineering from The Oklahoma State University, USA.
Brett Dodds
David McIntyre
Matthew Burns
Matthew Burns develops go-to-market strategies for Samtec’s Silicon-to-Silicon solutions. Over the course of 20+ years, he has been a leader in design, applications engineering, technical sales and marketing in the telecommunications, medical and electronic components industries. Mr. Burns holds a B.S. in Electrical Engineering from Penn State University.
Stephen Bates
Stephen is the VP and Chief Architect of Emerging Storage Systems at Huawei's Toronto Emerging Storage Lab. He and his team research all aspects of next-generation storage systems from media to programming interfaces to filesystems to virtualized storage to applications.
Stephen is an expert in performance storage, persistent and non-volatile memory, computer networking, signal processing and error correction coding. He is also very active in both the SNIA and NVM Express standard bodies.
Prior to Huawei he was the CTO of Eideticom which is a pioneer company in NVMe-based computational storage. He was also formerly in the CTO office at PMC-Sierra, an Assistant Professor at The Univeristy of Alberta and a Principal Engineer at Massana Inc. Stephen has a PhD from the University of Edinburgh and is a Senior Member of the IEEE.
Paul Crumley
Paul G Crumley, a Senior Technical Staff Member at IBM Research, enjoys creating systems to solve problems beyond the reach of current technology.
Paul’s current project integrates secure, compliant AI capabilities with enterprise Hybrid Cloud allowing clients to extract new business value from their data.
Paul’s previous work includes the design and construction of distributed, and high-performance computing systems at CMU, Transarc, and IBM Research. Projects include The Andrew Project at CMU, ASCI White, IBM Global Storage Architecture, Blue Gene Supercomputers, IBM Cloud, and IBM Cognitive Systems. Paul has managed data centers, and brings his first-hand knowledge of these environments, combined with experience of automation and robustness, to the design of AI for Hybrid Cloud infrastructure.