Ronald Seoh
Graduate Teaching Assistant
West Lafayette, Indiana, United States
Summary
👤
Senior🎓
Top SchoolRonald Seoh is a PhD student and Graduate Teaching Assistant at Purdue University with 11 years of professional experience spanning machine learning engineering, academic research, and quantitative finance. His research focuses on multimodal NLP and information retrieval, aiming to build systems that surface richer, more deliberative public opinion landscapes to improve cross-group dialogue and decision making. He has industry experience as an ML engineer at InMoment and practical research roles at UMass Amherst, plus earlier quantitative work in equity derivatives, giving him a rare blend of applied ML, research rigor, and product sensibility. Ronald also contributes to open-source documentation for notable projects like TensorFlow Federated, improving accessibility of federated learning tutorials for text and image tasks. Based in West Lafayette, he leverages interdisciplinary training—from LSE management science to CS degrees—to tackle how images and text jointly shape online persuasion and audience targeting.
11 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Purdue UniversityMaster of Science - MS, Computer Science, Master of Science - MS, Computer Science at University of Massachusetts AmherstLondon School of Economics and Political ScienceBachelor of Arts - BA, Computer Science, Business, Minor in Economics, Bachelor of Arts - BA, Computer Science, Business, Minor in Economics at Brandeis University
Github Skills (7)
user-manual10
jupyter-notebook10
learn-ruby-on-rails10
basics10
documentation10
federated-learning9
tensorflow7
Programming languages (5)
Github contributions (5)
google-parfait/tensorflow-federated
Oct 2020 - Oct 2020
An open-source framework for machine learning and other computations on decentralized data.
Role in this project:
Technical Writer
Technical WriterContributions:7 commits, 1 PR in 4 days
Contributions summary:Ronald primarily focused on improving the documentation and tutorials within the repository. Their commits involved fixing typos, making cosmetic changes, and correcting formatting issues in the tutorial notebooks related to federated learning for text generation and image classification. The user's contributions improved the clarity and readability of the tutorials, making them more accessible to others.
machine-learning
ronaldseoh/film_industry
Apr 2015 - Oct 2019
Contributions:11 pushes, 1 branch in 4 years 7 months
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