Vijay Dwivedi
Postdoctoral Scholar at Stanford University
San Francisco Bay Area United States
Summary
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Rockstar🎓
Top SchoolVijay Dwivedi is a Postdoctoral Scholar at Stanford with a decade of experience in multimodal foundation models, representation learning, and graph transformers, currently working in the SNAP group under Jure Leskovec. He previously led AI research at ASUS AICS driving medical ML applications and co-authored multiple recent papers on medical foundation models, clinical QA benchmarks, and robust medical summarization. His work blends scalable graph neural architectures (e.g., LargeGT) with practical healthcare deployments, and he has a strong track record of turning research prototypes into applied systems across industry and academia. Trained with a PhD from Nanyang Technological University, Vijay also brings leadership experience from large student organizations and cross-disciplinary internships in computer vision and NLP. Notably, he pairs deep theoretical work on graphs and multimodality with hands-on model development for clinical settings, reflecting a rare combination of academic rigor and product-focused impact.
10 years of coding experience
4 years of employment as a software developer
Bachelor’s Degree Computer Science and Engineering, Bachelor’s Degree Computer Science and Engineering at Motilal Nehru National Institute Of TechnologyHigher Secondary School (+2) Science, Higher Secondary School (+2) Science at Trinity International HSS/College, KathmanduDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Nanyang Technological University Singapore
English, Hindi, Nepali, Bhojpuri
Stackoverflow
23reputation
1kreached
1answer
1question
Github Skills (55)
transformers10
geometric-deep-learning10
representation-learning10
pytorch10
transformer-architecture10
gnn10
benchmarking10
keras10
message-passing10
deep-learning10
graph-neural-network10
graph-convolutional-networks10
graph-representation-learning10
dgl10
data-science9
Programming languages (5)
Github contributions (5)
graphdeeplearning/benchmarking-gnns
Mar 2020 - May 2022
Repository for benchmarking graph neural networks (JMLR 2023)
Contributions:40 commits, 18 PRs, 58 pushes in 2 years 2 months
benchmarkinggraph-neural-networkgraph-representation-learninggraph-neural-networksbenchmark-framework
vijaydwivedi75/Custom-Mask-RCNN_TF
Dec 2018 - Dec 2018
Contributions:12 commits, 9 pushes, 1 branch in 4 days
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