Yutian Pang
Postdoctoral Fellow at Cockrell School of Engineering, The University of Texas at Austin
Austin, Texas, United States
Summary
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Senior🎓
Top SchoolYutian Pang is a postdoctoral fellow at UT Austin with eight years of experience at the intersection of data-driven learning, simulation, and aerospace systems. He holds a PhD in Mechanical and Aerospace Engineering and has driven AI-for-ATM and prognostics research from concept to publication during a multi-year research appointment at Arizona State University. His industry experience includes machine learning and cybersecurity R&D at Thales and applied behavior prediction work during an internship at XPENG, blending academic rigor with practical engineering. On open source, he contributed to the well-known Cleverhans adversarial example library by improving the Momentum Iterative Method and hardening its loss implementation, reflecting hands-on expertise in adversarial robustness. Based in Austin, he combines simulation-informed modeling with data-centric ML and has experience applying LLMs and generative approaches to security and NLP problems. Colleagues rely on him to bridge complex aerospace problems and modern ML techniques to deliver reproducible, production-relevant research.
8 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD Mechanical and Aerospace Engineering, Doctor of Philosophy - PhD Mechanical and Aerospace Engineering at Arizona State UniversityBachelor's degree Mechanical Engineering Manufacturing and Automation, Bachelor's degree Mechanical Engineering Manufacturing and Automation at Huazhong University of Science and Technology
Chinese, English
Stackoverflow
1reputation
0reached
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Github Skills (7)
machine-learning10
adversarial-attacks10
tensorflow10
python10
security9
benchmark8
benchmarking8
Programming languages (2)
Github contributions (5)
cleverhans-lab/cleverhans
Mar 2021 - Mar 2021
An adversarial example library for constructing attacks, building defenses, and benchmarking both
Role in this project:
ML Engineer
ML EngineerContributions:5 commits, 1 PR, 7 comments in 1 day
Contributions summary:Yutian primarily focused on modifying and refining the Momentum Iterative Method (MIM) within the Cleverhans library. Their commits involved incorporating softmax cross-entropy loss, addressing reported bugs, and formatting the code to adhere to the black style guidelines. The user's contributions centered on enhancing the attack's functionality by incorporating a crucial loss function, directly improving the robustness of adversarial example generation.
benchmarkingrobustnessadversarial-machine-learningsecurityadversarial
ymlasu/para-atm-collection
Jul 2021 - Jan 2023
PARA-ATM Research Collection
Contributions:53 commits, 7 PRs, 64 pushes in 1 year 6 months
atm
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