94.0
David Z. Pan
Gilead Sciences (United States)
David Z. Pan has made significant contributions to various fields, including optics, machine learning, and electronics. Their research focuses on developing new technologies for scalable deep learning, such as integrated multi-operand optical neurons and differentiable edge-based OPC. Additionally, they have explored machine learning-assisted inverse stack-up optimization and applied reinforcement learning to circuit design. In the realm of photonic devices, Pan has developed tools like pace for accurate optical field simulation and elight for efficient in-memory computing. Their work also delves into analog/mixed-signal design automation with Bayesian neural networks and open-source frameworks for lithography imaging.
Firms applying this knowledge
Tela Innovations, Inc., International Business Machines Corporation, Synopsys, Inc., Taiwan Semiconductor Manufacturing Company Ltd., Asml Netherlands B.V., Globalfoundries U.S. Inc., Micron Technology, Inc., Xilinx, Inc., Fujitsu Limited, Cadence Design Systems, Inc., Oracle International Corporation, Center For Deep Learning In Electronics Manufacturing, Inc., Toshiba Memory Corporation, Freescale Semiconductor,Inc., Lattice Semiconductor Corporation, Sandisk Technologies Llc, Hip Innovations, Llc, Macronix International Co., Ltd., Carl Zeiss Meditec Ag, Nxp B.V., Canon Kabushiki Kaisha, Ati Technologies Ulc, Synplicity, Inc., Oregon Health And Science University, Lockheed Martin Corporation, Global Unichip Corporation, Intel Corporation, Mentor Graphics (Deutschland) Gmbh, Northwestern University, Hrl Laboratories, Llc, King Fahd University Of Petroleum And Minerals, Northrup Grumman Systems Corporation, National Yang Ming Chiao Tung University, Gist(Gwangju Institute Of Science And Technology), Kabushiki Kaisha Toshiba, Rutgers, The State University Of New Jersey, Microsoft Technology Licensing, Llc