Patricia Gonzalez

About Patricia Gonzalez

Dr. Patricia Gonzalez-Guerrero is a Research Scientist at Lawrence Berkeley National Laboratory. Her work spans ultra-low-power digital and mixed-signal SoC/ASIC/VLSI design for conventional and non-conventional forms of processing; Superconducting computing; Quantum readout and control; FPGAs/RISCV for exploration and evaluation of high-performance computing architectures; and hardware specialization through chiplets. She has three best paper awards and two awarded patents and is currently co-leading the HPC&AI chiplets modularity workstream in the Open Compute Project.

James Tandon

About James Tandon

Dr. James Tandon is the CEO and Founder of Cassia.ai, a semiconductor IP company that develops specialized computer arithmetic for AI accelerator chips to double their TOPs/watt efficiency, and a professor of Computer Engineering at CSU East Bay. Dr. Tandon received his bachelor, masters, and doctorate degrees from University of California, Santa Barbara. His initial PhD work focused on metrics for analysis for energy scalability of heterogenous multicore, multiprocessor systems. As a postdoctoral researcher at the University of Tokyo, his work shifted to stochastic data converters. He developed several time-to-digital converters with tunable precision down to less than 200fs. He also developed multiple equivalent-time analog to digital converters with effective sampling rates exceeding 5TS/s. Dr. Tandon then moved to Silicon Valley to work at Microsemi SoC (now Microchip Technologies) as an FPGA architect before returning to his roots in power-performance optimization of digital circuits and systems. His most recent research interest is in the application of superconductor devices to AI accelerators and the associated opportunities and challenges.

Hiu-Yung Wong

About Hiu-Yung Wong

Dr. Hiu Yung Wong is an Associate Professor at San Jose State University. He received his Ph.D. degree in Electrical Engineering and Computer Science from the University of California, Berkeley in 2006. From 2006 to 2009, he worked as a Technology Integration Engineer at Spansion. From 2009 to 2018, he was a TCAD Senior Staff Application Engineer at Synopsys. He received the Industry Sponsored Research Award and the ERFA RSCA Award in 2024, the AMDT Endowed Chair Award, the Curtis W. McGraw Research Award from ASEE Engineering Research Council in 2022, the NSF CAREER award and the Newnan Brothers Award for Faculty Excellence in 2021, and the Synopsys Excellence Award in 2010. He is the author of two books, "Introduction to Quantum Computing: From a Layperson to a Programmer in 30 Steps" and "Quantum Computing Architecture and Hardware for Engineers: Step by Step". He is one of the founding faculty members of the Master of Science in Quantum Technology at San Jose State University. His research interests include the application of machine learning in simulation and manufacturing, cryogenic electronics, quantum computing, and wide bandgap device simulations. His works have produced 1 book, 1 book chapter, more than 120 papers, and 10 patents.

Ahmedullah Aziz

About Ahmedullah Aziz

Dr. Ahmedullah Aziz is an Assistant Professor of Electrical Engineering & Computer Science at the University of Tennessee, Knoxville, USA. He earned his Ph.D. in ECE from Purdue University in 2019, an MS degree in EE from the Pennsylvania State University in 2016, and a BS degree in EE from Bangladesh University of Engineering & Technology in 2013. He received several awards and accolades for his research, including the ‘Translational Research Award’ & ‘Chancellor’s Innovation Award’ from UT Knoxville (2024), ‘New Faculty Researcher Award’ from American Society of Engineering Educators (2024), 'ACM SIGDA Outstanding Ph.D. Dissertation Award (2021)' from the Association of Computing Machinery, 'Outstanding Graduate Student Research Award (2019)' from Purdue University, and 'Icon' award from Samsung (2013). He is a technical program committee (TPC) member for multiple flagship conferences (including DAC and ISCAS), and a reviewer for several reputed journals (including Nature, Advanced Materials). He serves as an editorial board member for multiple journals including - 'Scientific Reports', and the ‘Journal of Applied Physics'. He also served as a review panelist for the US Department of Energy, and the National Science Foundation (NSF). Dr. Aziz is an expert in device-circuit co-design and electronic design automation (EDA). His research portfolio comprises multiple avenues of nanoelectronics, spanning from device modeling to circuit/array design. Dr. Aziz has been a trailblazer in cryogenic memory technologies, facilitating critical advancements in quantum computing systems and space electronics.