Summary
Philip Wang is a Principal Engineer with nine years of experience at the intersection of machine learning, computational physics, and backend software, currently driving advanced EDA and RET capabilities at Siemens EDA. His background includes R&D leadership in etch and MEC modeling at Synopsys and hands-on development of inverse lithography and Calibre machine-learning integrations, blending deep academic rigor from a Yale PhD with production-grade engineering. He also pairs backend systems experience and blockchain experimentation (TON) from his GitHub work, demonstrating a breadth from high-performance numerical simulation to scalable software. An Australian citizen eligible for a US E3 visa, he brings a rare combination of experimental lab skills, large-scale simulation coding (C++, Python/Numba), and product-focused R&D leadership that accelerates bringing research into industry tools.
9 years of coding experience
10 years of employment as a software developer
Master of Science (MS) Mechanical Engineering, Master of Science (MS) Mechanical Engineering at University of Southern California
Bachelor of Science (BS) Mechanical Engineering, Bachelor of Science (BS) Mechanical Engineering at National Cheng Kung University
Doctor of Philosophy (PhD) Mechanical Engineering and Materials Science, Doctor of Philosophy (PhD) Mechanical Engineering and Materials Science at Yale University
JYPE 10-11 Mechanical Engineering, JYPE 10-11 Mechanical Engineering at Tohoku University
English, Chinese, Japanese