Zhaoyi Hou is a PhD student in computer science at the University of Pittsburgh and an applied scientist focused on advancing NLP and commonsense reasoning through practical, benchmark-driven research. With eight years of experience across academic labs and industry, they built a RAG QA pipeline that notably improved USMLE accuracy and now work on Amazon's ML stack leveraging AWS SageMaker and production-focused tooling. Their background blends data science training from UPenn and UCSD with hands-on projects—ranging from transformer-based patent prediction and clinical image pipelines to large-scale ETL for behavioral text analysis—demonstrating both research rigor and production engineering. Known for distilling large models into usable systems (e.g., knowledge distillation from GPT-3) and shipping measurable gains, Zhaoyi pairs deep modeling expertise with practical data engineering to push NLP toward real-world impact.
8 years of coding experience
4 years of employment as a software developer
High School, High School at Guangzhou Zhixin High School
University of California, San Diego
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of Pittsburgh School of Computing and Information
Master of Science in Engineering (MSE) Data Science, Master of Science in Engineering (MSE) Data Science at University of Pennsylvania
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