Our Cast
Norman Chang
Semiconductor BU, ANSYS
Norman Chang co-founded Apache Design Solutions in February 2001 and currently serves as Ansys Fellow and Chief Technologist of Electronics, Semiconductor, and Optics BU, ANSYS, Inc. He is also currently leading AI/ML and security initiatives at ANSYS. Prior to Apache, he lead a research group on Power/Signal/Thermal Integrity of chipsets based on VLIW architecture at HP Labs. Dr. Chang received his Ph.D. in Electrical Engineering and Computer Sciences from University of California, Berkeley. He holds 25 patents and has co-authored over 60 IEEE papers and a popular book on
Pradeep Dubey
Intel
Pradeep K. Dubey is an Intel Senior Fellow and director of the Parallel Computing Lab, a part of the Intel Labs organization at Intel Corporation. He leads a team of top researchers focused on state-of-the-art research in parallel computing. Dubey and his team are responsible for defining computer architectures that can efficiently handle emerging machine learning/artificial intelligence, traditional HPC applications for data-centric computing environments, and deriving product differentiation opportunities for Intel's CPU and GPU processing platforms. Dubey previously worked at IBM's T.J. Watson Research Center. Dubey has made significant contributions to the design, architecture and application performance of various microprocessors, including the IBM Power PC, the Intel386(tm), Intel486(tm), Intel Pentium, and Intel Xeon processors. He holds 36 patents and has published more than 100 peer-reviewed technical papers. In 2012, Dubey was honored with an Intel Achievement Award for breakthroughs in parallel computing research, and was honored with Outstanding Electrical and Computer Engineer Award from Purdue University in 2014. Dubey holds a Ph.D. in electrical engineering from Purdue University. He is a Fellow of IEEE and also an ACM Fellow.
Vishal Khandewal
Synopsys
Vishal is a Chief Architect in the EDA Group at Synopsys leading the Fusion Compiler physical optimization team. He has extensive R&D experience in state-of-the-art Place&Route engines and flows, including applying machine-learning techniques to improve PPA and runtime. Vishal has a Ph.D. from University of Maryland and has authored over 30 patents and IEEE/ACM publications, including best paper winners at DAC-2023, ISPD-2021 and ISPD-2007.
Ala Moradian
Applied Materials
Ala Moradian is a director at the Computational Product and Solutions (CPS) Center of Excellence at Applied Materials where he is focused on epitaxy technology and digital twins for semiconductor manufacturing. Over more than a decade at Applied, Ala has worked on different products and business units such as ion implant, rapid-thermal processing, epitaxy, physics-based simulation and led the development of several new technologies and products. His roles included CFD expert, heat transfer subject matter expert, scientist/physicist, program lead and product manager. He is also the intellectual property technologist for Epitaxy business unit at Applied Materials. Ala obtained his PhD in mechanical engineering from University of Toronto, a master's from Sharif University of technology, and a Masters in management from Harvard University. Ala is a Fellow of American Society of Mechanical Engineers (ASME), and an adjunct faculty at UC Berkeley. He has over 20 publications and over 70 US patents and applications.
Ronjon Nag
Stanford Medicine
Dr. Ronjon Nag, Adjunct Professor, Stanford Medicine; President R42 Group. Ronjon Nag has been building AI systems for 40 years and co-founded or advised companies sold to Motorola, RIM/BlackBerry, and Apple. He is a venture capitalist with his firm R42, which invests in AI and longevity companies. He became a Stanford Interdisciplinary Distinguished Careers Institute Fellow in 2016. He teaches AI, genes, and ethics courses at Stanford Medicine. He received a PhD from Cambridge, an MS from MIT, the IET Mountbatten Medal, the $1 million Verizon Powerful Answers Award, and the 2021 IEEE-SCV Outstanding Engineer Award.
Dr. Nag is the 2024 inductee into the Silicon Valley Engineering Hall of Fame. He is part owner of some 100 AI and biotech startups.
Chandrakant Patel
HP
Chandrakant Patel, HP
Haowing Ren
NVidia
Haoxing (Mark) Ren is the Director of Design Automation Research at NVIDIA, focusing on leveraging machine learning and GPU-accelerated tools to enhance chip design quality and productivity. He has over 20 years of industrial EDA research experience at IBM Research and NVIDIA Research. He holds over twenty patents and has co-authored over 100 papers and books, including a book on ML for EDA and several book chapters in EDA. He received several prestigious awards for his work, including the IBM Corporate Award and best paper awards at ISPD, DAC, TCAD, MLCAD, and LAD. He earned his Ph.D. from the University of Texas at Austin and is a Fellow of the IEEE.
Naresh Sehgal
Deeply Human AI
Naresh K. Sehgal is currently the CTO at Deeply Human AI, Inc. Before that he worked at NovaSignal for 3 years and at Intel for 31 years in various Engineering and Management roles. Naresh has earned his B.E. from Punjab Engineering College, M.S. and Ph.D. from Syracuse University. He taught a Cloud Computing class at Santa Clara University and earned an MBA. Naresh has 7 patents, co-authored 5 books, and published 40 technical papers in various conferences and journals
Jianjun Xu
Keysight
Dr. Jianjun Xu is recognized internationally as a leading innovator of advanced artificial neural network (ANN) technology and its practical applications to a wide range of microwave and RF engineering problems. He is presently Senior Machine Learning Engineer at Keysight Laboratories, Keysight Technology, Inc., in Santa Rosa CA. His ANN research has been integrated into leading commercial simulators and measurement-based design flows, including transistor characterization and nonlinear modeling of GaAs and GaN FETs, cryogenic CMOS devices, lithium-ion battery models, TCAD-to-circuit links, and more. Dr. Xu received the Ph.D. Degree in Electrical Engineering from Carleton University, Ottawa, Canada, in 2004, and is a frequent technical reviewer for the IEEE on topics of AI/ML and ANNs.