Zihan Wang
Postdoctoral Scholar at Northwestern University
Greater Chicago Area United States
Summary
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Rockstar🎓
Top SchoolZihan Wang is a Postdoctoral Scholar at Northwestern University specializing in data-driven design and materials informatics, with a PhD in Mechanical Engineering from the University of Connecticut. He combines deep learning (PyTorch, TensorFlow) with advanced simulation tools (SolidWorks, UG NX, Abaqus, LS-DYNA, Pro-CAST) to optimize designs under uncertainty and for manufacturability. His work blends uncertainty quantification and propagation with practical engineering workflows, demonstrated during a GE Research fellowship tackling probabilistic methods for industry problems. With high academic distinction and bilingual training in engineering and translation, he bridges technical depth and clear cross-disciplinary communication. Based in the Greater Chicago Area, he brings three years of focused research experience and prior collaborations at Deepseek-AI and UIUC NLP that reflect a broad interest across AI and engineering. Notably, he pairs rigorous simulation expertise with modern ML to move materials design from theory toward manufacturable solutions.
3 years of coding experience
Doctor of Philosophy - PhD, Mechanical Engineering, 4.066/4.0, Doctor of Philosophy - PhD, Mechanical Engineering, 4.066/4.0 at University of ConnecticutBachelor of Engineering - BE, Material Processing and Control Engineering, 3.89/4.0, Bachelor of Engineering - BE, Material Processing and Control Engineering, 3.89/4.0 at Huazhong University of Science and Technology
Github Skills (32)
pytorch10
llama10
inference10
tpu10
amd10
llm10
llmops10
language-modeling10
ranking10
cuda10
transformer10
gpt10
transformer-architecture10
reinforcement-learning9
xpu9
Programming languages (4)
Github contributions (5)
ZihanWang314/ZihanWang314.github.io
Aug 2022 - Jan 2023
Contributions:19 commits, 146 pushes in 4 months
ZihanWang314/NOVO
Sep 2023 - Jan 2025
Contributions:3 pushes, 1 branch, 1 issue in 1 year 4 months
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