Han Guo
Research Intern at Together AI
United States
Summary
👤
Senior🎓
Top SchoolHan Guo is a research-oriented machine learning and NLP engineer with nine years of experience bridging academic rigor and industry research, currently pursuing a PhD in EECS at MIT and interning at Together AI. He has held research internships at leading labs including IBM MIT-IBM Watson, Salesforce AI Research, Baidu Research, and contributed to UNC’s NLP lab under Mohit Bansal. Han’s practical contributions include refactoring and improving the uncertainty-toolbox for predictive uncertainty quantification, showing attention to reproducible metrics and calibration in ML systems. Comfortable moving between code and research, he has a track record of cleaning, modularizing, and improving tooling that supports model evaluation. His background spans CS and statistics at UNC and specialized language/IT studies at Carnegie Mellon, reflecting a strong foundation in both theory and applied NLP. Colleagues note his blend of careful engineering and research curiosity, often improving existing functionality rather than reinventing it.
9 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD EECS, Doctor of Philosophy - PhD EECS at Massachusetts Institute of TechnologyHigh School International Baccalaureate Diploma Program, High School International Baccalaureate Diploma Program at Weiyu High School International DivisionLanguage and Information Technology, Language and Information Technology at Carnegie Mellon UniversityBachelor’s Degree Computer Science Statistics, Bachelor’s Degree Computer Science Statistics at University of North Carolina at Chapel Hill
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (8)
calibration10
python10
metric10
numpy9
uncertainty-quantification9
bayesian-network9
visualizations7
visualization7
Programming languages (7)
Github contributions (5)
uncertainty-toolbox/uncertainty-toolbox
Nov 2020 - Dec 2020
Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
Role in this project:
Data Scientist
Data ScientistContributions:12 commits in 20 days
Contributions summary:Han primarily contributed to the `uncertainty-toolbox` by cleaning and refactoring code related to metrics and calibration, focusing on improvements to existing functionality. They updated the metrics module by extracting the argument parser and cleaning imports. There were also minor style improvements made to the data and recalibration modules, with removed and unused variable.
pythonpython-toolboxpredictive-uncertaintyvisualizationsrecalibration
HanGuo97/Reading-List
Jun 2018 - Jan 2020
Contributions:54 commits, 46 pushes, 1 branch in 1 year 6 months
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