Kawin Ethayarajh
PhD Student at Stanford University
Old Toronto, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolKawin Ethayarajh is a PhD student at Stanford with 11 years of experience building and researching NLP systems, particularly in representation learning and fairness. He has a proven track record from University of Toronto research—authoring state-of-the-art unsupervised sentence embeddings and a high-accuracy citation prediction model—to applied work at Google where he shipped a zero-shot relation extraction pipeline that improved precision notably. Kawin contributes to prominent open-source ML tooling such as Hugging Face’s trl repo, where he optimized the KTO trainer and improved robustness and documentation for RL-based language model training. Based in Toronto, he blends deep academic rigor with practical engineering, comfortable taking projects from theoretical insight to production pipelines. An understated strength is his pattern of extracting clear signals from noisy social and legal text corpora, including seasonal sentiment effects across Reddit users.
11 years of coding experience
9 years of employment as a software developer
Master of Science - MSc Computer Science, Master of Science - MSc Computer Science at University of Toronto
Github Skills (7)
transformer-models10
huggingface-transformers10
pytorch10
machine-learning10
nlp10
python10
reinforcement-learning10
Programming languages (5)
Github contributions (5)
huggingface/trl
Jan 2024 - Oct 2024
Train transformer language models with reinforcement learning.
Role in this project:
ML Engineer
ML EngineerContributions:5 reviews, 10 PRs, 53 comments in 8 months
Contributions summary:Kawin primarily contributed to the `trl` repository, which focuses on training transformer language models with reinforcement learning. Their work centered on the KTO (knowledge transfer optimization) trainer, specifically addressing bugs, implementing features, and optimizing performance. The user's contributions included bug fixes, metric additions, and code improvements. They also addressed the KTO implementation, included warnings for data imbalances and updated documentation to streamline the training process.
nlptransformer-architecturelanguage-modelfinetuninglanguage-modeling
kawine/kawine.github.io
Apr 2019 - Aug 2022
Contributions:79 commits, 141 pushes, 1 branch in 3 years 4 months
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