Mingwei Ge is a research-driven scientist-engineer with eight years of experience at the intersection of chemistry, physics, and machine learning, currently pursuing a PhD in Electrical Engineering at Yale. He develops and applies computational and experimental techniques—ranging from ab-initio calculations and transient spectroscopy to graph neural networks and active learning—to advance organic-inorganic hybrid semiconductor photodetectors and spin dynamics studies. His work spans academic and industry settings, including a Samsung internship where he built generative models to design TADF molecules for OLEDs by coupling GNNs with DFT and post-HF calculations. Based in New Haven, he blends hands-on lab skills with ML-driven model development to solve materials challenges, often integrating full-stack workflows that accelerate discovery and device optimization.
8 years of coding experience
2 years of employment as a software developer
Beijing Huiwen Middle School
Bachelor of Science - BS, Chemistry, Bachelor of Science - BS, Chemistry at Nankai University
Doctor of Philosophy - PhD, Electrical Engineering, Doctor of Philosophy - PhD, Electrical Engineering at Yale University
Contributions:9 pushes, 3 branches in 3 years 8 months
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