Arjun Subramonian is an inclusive Graph ML and NLP researcher and PhD candidate at UCLA with about 10 years of experience building ML systems, fairness tooling, and production features. He bridges research and engineering—contributing to the widely used AllenNLP library (including a fairness library, bias mitigation methods, and ports for transformer schedulers) and interning at Meta FAIR, Microsoft FATE, Snap, and AI2 on problems spanning graph expressivity, NLP conceptualization, privacy, and safety. His applied work ranges from shipping harassment-reporting features and routing optimizations in production to developing in-house deep models for behavior analysis. Less obvious is that he designed a neural network for rapid antimicrobial susceptibility testing that achieved FDA-essential agreement, and he co-founded QWER Hacks, the first student-organized LGBTQIA+ hackathon in the U.S., reflecting strong commitments to impactful research and inclusive outreach. Based in New York, he pairs open-source impact with interdisciplinary research and community leadership.
10 years of coding experience
3 years of employment as a software developer
Concurrent Enrollment, Mathematics, GPA: 4.00, Concurrent Enrollment, Mathematics, GPA: 4.00 at De Anza College
Concurrent Enrollment, Mathematics, GPA: 4.00, Concurrent Enrollment, Mathematics, GPA: 4.00 at Foothill College
UW/W GPA: 3.98/4.50, UW/W GPA: 3.98/4.50 at Monta Vista High School
University of Illinois Urbana-Champaign
3.940, 3.940 at University of California, Los Angeles
An open-source NLP research library, built on PyTorch.
Role in this project:
ML Engineer
Contributions:57 reviews, 16 commits, 23 PRs in 2 months
Contributions summary:Arjun's contributions primarily revolve around updating and enhancing AllenNLP, an open-source NLP library built on PyTorch. Their work includes documenting and updating components related to softmax loss, setting transformers to evaluation mode within the library, and porting Huggingface LambdaLR-based schedulers. Additionally, the user has worked on fairness metrics, and implemented bias mitigation techniques and methods, suggesting a focus on improving and extending NLP capabilities.
Contributions:1 PR, 119 pushes, 1 branch in 4 years 7 months
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