Changhong Zhang
New York City Metropolitan Area United States
Summary
👤
Senior🎓
Top SchoolChanghong Zhang is an applied ML researcher and engineer with nine years of experience building production-ready AI systems and a strong academic foundation in statistics and data science. As a Research Assistant at GWU’s I²SDS he implemented a novel layer-wise GPT distillation using Wasserstein distance that improved perplexity and stability, and contributed to multiple peer-reviewed papers on ML-driven optimization. He designs reproducible, cloud-native ML templates and teaching materials—supporting 150+ students—and has productionized RAG and agentic pipelines (OCR, BM25+FAISS retrieval, reranking) into Dockerized AWS services. Changhong blends competition-grade feature engineering (Top 2% in an AmEx Kaggle challenge) with practical tooling for experiment management, A/B sandboxes, and lightweight serving, and he is particularly focused on LLM optimization, decision-making in dynamic environments, and financial time-series modeling.
8 years of coding experience
Doctor of Philosophy - PhD Decision Sciences specializing in LLM and ML, Doctor of Philosophy - PhD Decision Sciences specializing in LLM and ML at The George Washington UniversityBachelor of Science - BS Statistics, Bachelor of Science - BS Statistics at Guangzhou University
Chinese, Chinese, English
Github Skills (19)
aio9
dpdk8
server-side8
async8
replay8
server7
incremental-learning7
high-performance6
http-server6
deep-learning6
machine-learning6
reproducible-research6
pytorch6
seastar5
toolbox5
Programming languages (3)
Github contributions (5)
zhchuu/continual-learning-reproduce
Apr 2020 - Jun 2022
Continual / incremental / lifelong learning methods implemented by PyTorch. Especially the methods based on memory replay.
Contributions:34 commits, 33 pushes, 1 branch in 2 years 2 months
pytorchmemoryincrementalreplaydeep-learning
zhchuu/zhchuu.github.io
Jun 2020 - Mar 2025
Contributions:67 pushes, 1 branch in 4 years 9 months
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