Junlin Wang is a PhD candidate in Computer Science at Duke University with 11 years of industry and research experience focused on NLP, particularly QA, retrieval, text generation, interpretability, and robustness. He has applied his research in internships at Together AI, AWS, Intel, Tencent, and Comcast and contributed to open-source explainability work (co-author on an EMNLP demo award-winning AllenNLP Interpret paper). His background includes building open-domain QA systems, designing adversarial attacks against NLP models, and experimenting with GNNs for large-scale payment data, showing a blend of theoretical rigor and production-minded engineering. Based in Durham, NC, Junlin brings deep academic training and practical deployment experience to challenges at the intersection of research and applied ML.
11 years of coding experience
4 years of employment as a software developer
High School, High School at Dwight-Englewood School
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Duke University
An open-source NLP research library, built on PyTorch.
Contributions:40 commits, 9 pushes, 5 branches in 1 year 9 months
pytorchnlpbertdeep-learningmachine-learning
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