Shichang Zhang
Postdoctoral Fellow at Harvard Business School
Los Angeles, California, United States
Summary
👤
Senior🎓
Top SchoolShichang Zhang is a Postdoctoral Fellow at Harvard with a Ph.D. in Computer Science from UCLA and nine years of industry and research experience spanning explainable AI, post-training LLMs, and human-AI alignment. His interdisciplinary training in statistics (Stanford MS, Berkeley BA) informs a rigorous, data-driven approach to model interpretability and graph-based learning. During his Ph.D. he secured competitive industry fellowships from J.P. Morgan Chase and Amazon and completed influential internships at AWS and Snap that produced papers at WWW and ICLR on GNN explanation and distillation. He teaches and mentors students, has built production-oriented pipelines and models in industry settings, and now studies how post-hoc methods can make large models more trustworthy in real-world deployments. Notably, his work bridges theory and practice—turning research prototypes into published, deployable solutions for graph ML and AI explainability.
9 years of coding experience
5 years of employment as a software developer
Bachelor of Arts - BA, Statistics, Bachelor of Arts - BA, Statistics at University of California, BerkeleyDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of California, Los AngelesMaster of Science - MS, Statistics, Master of Science - MS, Statistics at Stanford University
Chinese, English
Github Skills (26)
graph-representation-learning8
mining7
self-supervised-learning7
generative6
xai6
graph-neural-network5
deep-learning5
datasets5
machine-learning5
graph5
benchmark4
pytorch4
python4
finder4
data-analysis3
Programming languages (3)
Github contributions (5)
ShichangZh/ShichangZh.github.io
Aug 2016 - Nov 2019
Contributions:81 commits, 134 pushes, 2 branches in 3 years 3 months
ShichangZh/GStarX
Jul 2022 - Oct 2022
Contributions:8 commits, 2 pushes, 6 comments in 2 months
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