Alex Wang
PhD Student at New York University
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolAlex Wang is a PhD student in computer science at NYU with 11 years of hands-on experience applying deep learning to natural language and vision problems, advised by Kyunghyung Cho and Sam Bowman. He holds a BA in Applied Mathematics (magna cum laude) and an MS in Computer Science from Harvard, where he built language models, an abstractive summarizer, and researched one-shot learning and adversarial attacks on vision systems. Alex contributes to open-source NLP tooling—helping implement and refactor key model components and dataset support in the widely used jiant toolkit—demonstrating strengths in model architecture, data handling, and task-specific engineering. He has published and interned at top research labs (Stanford, Microsoft) and combines rigorous academic training with practical software development, including an R package on CRAN and automated AWS workflows for data collection. Notably, his background spans both teaching leadership roles with high student ratings and production-ready engineering contributions, reflecting an ability to communicate complex ideas and ship reliable research code.
11 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at New York UniversityBachelor's degree, Applied Mathematics, magna cum laude with high honors, Bachelor's degree, Applied Mathematics, magna cum laude with high honors at Harvard UniversityHigh School, High School at Libertyville High School
Github Skills (11)
pytorch10
machine-learning10
nlp10
architectures10
modeling10
architecture10
python9
data-handling9
transformers8
bert8
multi-task-learning7
Programming languages (4)
Github contributions (5)
nyu-mll/jiant
Mar 2019 - May 2020
jiant is an nlp toolkit
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:1 release, 63 commits, 120 PRs in 1 year 2 months
Contributions summary:Alex primarily contributed to the NLP toolkit by implementing and refactoring various model components. Their work includes adding a first-state pooling mechanism, refactoring pair sentence attention, and removing obsolete attributes from the pooler module. They also addressed data loading issues for tasks like MNLI and added support for the new BoolQ dataset. Their contributions suggest a focus on model architecture, data handling, and task-specific implementations within the NLP domain.
nlptransformersmultitask-learningsentence-representationbert
W4ngatang/DocumentSummarizer
Apr 2016 - May 2016
Contributions:38 commits, 27 pushes, 1 branch in 20 days
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