Daning Huang
Assistant Professor at Penn State University
Ann Arbor, Michigan, United States
Summary
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Rockstar🎓
Top SchoolDaning Huang is an Assistant Professor of Aerospace Engineering at Penn State with a decade of experience bridging computational methods and experimental design in high-speed aerothermoelasticity. He develops coupled fluid–structure–thermal frameworks—combining nonlinear finite elements, multi-fidelity CFD, and efficient coupling schemes—to analyze hypersonic panel response and inform scaled experiments via multi-objective Bayesian optimization. Trained at the University of Michigan (PhD) and fluent in both academic research and practical engineering, he also applies computer science techniques to aeronautical problems and contributes to open-source projects like the differentiable-robotics pypose library where he improved dynamics modules and documentation. Based in Ann Arbor, his work sits at the intersection of structural dynamics, fluid dynamics, and computational tools, with a knack for translating complex multiphysics models into usable software and testable designs.
10 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Aerospace Engineering, Doctor of Philosophy (Ph.D.), Aerospace Engineering at University of MichiganBachelor of Engineering (BEng), Aerospace, Aeronautical and Astronautical Engineering, 4.4/5.0, Bachelor of Engineering (BEng), Aerospace, Aeronautical and Astronautical Engineering, 4.4/5.0 at Nanjing University of Aeronautics and AstronauticsSuzhou High School
Github Skills (6)
pytorch10
python10
documentation10
robotics9
optimization8
controlling7
Programming languages (3)
Github contributions (5)
pypose/pypose
Jul 2022 - Aug 2022
A library for differentiable robotics.
Role in this project:
Back-end Developer & Documentation Specialist
Back-end Developer & Documentation SpecialistContributions:26 reviews, 14 commits, 13 pushes in 25 days
Contributions summary:Daning primarily contributed to the `pypose/pypose` library, focusing on the `dynamics` module. Their work involved adding detailed documentation, including comments and expanded explanations for classes and arguments. The user also made code adjustments, such as correcting typos and providing examples of using the classes.
pytorchroboticspythongeometric-deep-learningcomputer-graphics
smanist/smanist.github.io
Mar 2017 - May 2020
Contributions:146 pushes, 1 branch in 3 years 1 month
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