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Wei Jin

analysis

domain adaptation

fine-tuning

automatic evaluation

graph neural networks

text-to-text generation

data-centric ai

table qa

math qa

efficient learning

commonsense qa

few-shot qa

model bias/unfairness mitigation

llm decision-making

1

presentations

10

number of views

SHORT BIO

Wei Jin is an Assistant Professor of Computer Science at Emory University. He obtained his Ph.D. from Michigan State University in 2023. His research focuses on graph machine learning and data-centric AI, with notable accomplishments such as AAAI New Faculty Highlights, KAUST Rising Star in AI, Snap Research Fellowship, Most Influential Papers in KDD and WWW by Paper Digest, and top finishes in three NeurIPS competitions. He has organized tutorials and workshops at top conferences, and published in top-tier venues such as ICLR, KDD, ICML, and NeurIPS. He has served as (senior) program committee members at these conferences and received the WSDM Outstanding Program Committee Member award.

Presentations

Empowering Graph Neural Networks from a Data-Centric View

Wei Jin

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