Xiaomeng Shen is a software engineer at Meta with a 9-year background bridging materials science Ph.D. research and applied engineering for semiconductor manufacturing. She combines deep hands-on expertise in thin-film characterization and device processing (HR-XRD, TEM, DLTS, ALD, RIE) with statistical data analysis and practical machine learning experience from developing CNNs to detect measurement artifacts. At KLA-Tencor she translated domain knowledge into customer-facing analytics and mentoring, defining critical yield metrics and coordinating cross-functional solutions for US fabs. Her academic work produced record improvements in carrier lifetime and detector dark current, reflecting an unusual ability to close the loop from growth and characterization to device performance. Based in New York, she brings a rare mix of experimental rigor, data-driven software development, and clear technical communication across research, product, and manufacturing contexts.
9 years of coding experience
10 years of employment as a software developer
SCPD student, SCPD student at Stanford University
Doctor of Philosophy (Ph.D.), Materials Science, 3.93/4.00, Doctor of Philosophy (Ph.D.), Materials Science, 3.93/4.00 at Arizona State University
NO.1 Middle School affiliated to Central China Normal University
Bachelor of Science (BS), Materials Science and Engineering, Bachelor of Science (BS), Materials Science and Engineering at Shanghai Jiao Tong University
Contributions:15 pushes, 1 branch in 2 years 4 months
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