Jinghui Chen
Assistant Professor at Penn State University
Los Angeles, California, United States
Summary
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Senior🎓
Top SchoolJinghui Chen is a tenure-track Assistant Professor at Penn State’s College of Information Sciences and Technology with 11 years of experience bridging trustworthy machine learning research and education. Trained with PhD work at UCLA and the University of Virginia and a bachelor’s from the University of Science and Technology of China, she leads the Trustworthy Machine Learning Lab focused on reliable, interpretable AI. Based in Los Angeles, she combines rigorous academic scholarship with practical lab-driven projects that aim to make ML systems safer and more accountable. Her profile reflects a rare mix of deep theoretical grounding and hands-on lab leadership, positioning her to translate research into real-world trustworthy AI practices.
12 years of coding experience
Bachelor's degree, Electronic Engineering and Information Science, Bachelor's degree, Electronic Engineering and Information Science at University of Science and Technology of ChinaDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of California, Los AngelesDoctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at University of Virginia
德语, Chinese
Github Skills (34)
visualization10
standardized10
bootstrapping10
analytics10
gradient10
forecasts10
github-pages10
adam10
data-access10
atmospheric-modelling9
ranking8
robustness8
mnist7
science7
react7
Programming languages (2)
Github contributions (5)
jinghuichen/covid19-forecast-hub
May 2020 - May 2021
Projections of COVID-19, in standardized format
Contributions:80 pushes in 1 year
projectionsstandardized
uclaml/Padam
Jun 2018 - Oct 2020
Partially Adaptive Momentum Estimation method in the paper "Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks" (accepted by IJCAI 2020)
Contributions:16 commits, 18 pushes, 6 comments in 2 years 4 months
deep-neural-networksadaptivegradientadaptive-gradient-methodadam
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