Vijay Prakash Dwivedi

VIJAY PRAKASH DWIVEDI [GitHub](https://github.com/vijaydwivedi75) [Twitter](https://twitter.com/vijaypradwi) [LinkedIn](https://linkedin.com/in/vijay321/) # About Postdoctoral Scholar, Stanford University Computer Science Department Group: SNAP Email: vdwivedi [AT] cs.stanford.edu ## Interests Machine Learning, Understanding Graphs and Structured Data, Large Language Models ## Bio I am a Postdoctoral Scholar at Stanford University working with Jure Leskovec in SNAP group on graph representation learning. Prior to this, I was an AI Researcher at ASUS Intelligent Cloud Services (AICS) in Singapore developing advanced AI capabilities using machine learning, large language models and multimodal deep learning for healthcare applications. I completed my PhD at Nanyang Technological University (NTU), Singapore, where I was advised by Luu Anh Tuan and Xavier Bresson and received one of the Outstanding PhD Thesis Awards. ## Education ### Doctor of Philosophy (PhD) - Nanyang Technological University (NTU), Singapore [Website](http://ntu.edu.sg/) Duration: 2019-2024 College of Computing and Data Science ### Bachelor of Technology (BTech) - Motilal Nehru National Institute of Technology (MNNIT), Allahabad [Website](http://mnnit.ac.in/) Duration: 2014-2018 Department of Computer Science and Engineering ## Research Experience Full Profile: [LinkedIn](https://www.linkedin.com/in/vijay321/) - Postdoctoral Scholar, [Stanford University, USA](https://snap.stanford.edu) (Nov 2024-now) - AI Researcher, [ASUS Intelligent Cloud Services (AICS), Singapore](https://aics.asus.com) (Dec 2023-Oct 2024) - Research Intern, [Snap Inc., Seattle, USA](https://research.snap.com) (Jun-Aug 2023) - Research Intern, [Sea AI Lab, Singapore](https://sail.sea.com) (Dec 2022-May 2023) - Research Intern, [Sony Group Corporation, Tokyo, Japan](https://www.sony.com/en/SonyInfo/research/) (Jun-Aug 2022) - Research Assistant, [Media & Interactive Computing Lab, NTU Singapore](https://www.ntu.edu.sg/computing/research/institutes-centres/micl) (Feb-Jul 2019) - Solution Consultant, [Francium Technologies Pvt Ltd, Chennai](https://francium.tech/) (Dec 2018-Feb 2019) - [Blog Post](https://blog.francium.tech/object-detection-on-documents-with-mask-rcnn-on-tensorflow-c7556654c167) - Research Intern, [Language Technologies Research Center (LTRC), IIIT Hyderabad](https://ltrc.iiit.ac.in/) (May-Jul 2017) - [Code Repository](https://github.com/vijaydwivedi75/Beyond_word2vec) - Research Intern, [CogBID Lab, University of Stirling](https://cogbid.github.io/) (May-Jul 2017) ## Publications [Google Scholar Profile](https://scholar.google.com/citations?user=8MS7iC0AAAAJ&hl=en) ## Keynotes, Talks and Tutorials ### ACM KDD 2025, Toronto, Canada (Aug 2025) Tutorial: Relational Deep Learning: Challenges, Foundations, and Next Generation Architectures - [Materials](https://sites.google.com/view/rdltutorial2025) ### Kumo.AI Virtual Workshop, Stanford, CA, USA (Feb 2025) Talk: Graph Transformers: What every data scientist should know - [Video](https://youtu.be/wAYryx3GjLw?si=0tsIX5ppXCn3rUJ8) ### 5th NAAMII Nepal Winter School in AI, Kathmandu, Nepal (Dec 2024) Lecture: Introduction to Graph Transformers ### Master of Computer Science (MCS) Program at Lincoln International College, Kathmandu, Nepal (Feb 2024) Guest Lecture: Learning on Graphs for Artificial Intelligence ### ML on Graphs (MLoG) Workshop at the 16th ACM International WSDM Conference, Singapore (Mar 2023) Keynote: Transformers for Graph Structured Data ### NTU Course MH6812: Advanced Natural Language Processing with Deep Learning (Feb 2023) Guest Lecture: Introduction to Graph Neural Networks ### 4th NAAMII Nepal Winter School in AI, Kathmandu, Nepal (May 2022) Introduction to GNNs ### 3rd NAAMII Nepal Winter School in AI, Kathmandu, Nepal (Dec 2021) Introduction to GNNs ### LoGaG: Learning on Graphs and Geometry Reading Group, Virtual (Nov 2021) Graph Neural Networks with Learnable Structural and Positional Representations - [Video](https://youtu.be/fft2Q0jEWi0) - [Slides](https://hannes-stark.com/assets/VPDwivedi_GNN_LSPE_LoGaG_2021.pdf) ### 4th National Workshop on Machine Learning and Data Science, Kathmandu, Nepal (Sep 2021) Introduction to GNNs and Application Prospects ### The DECAL Lab, UC Davis (Apr 2021) Benchmarking Graph Neural Networks ### NTU SCSE-GSC Student Lecture Series (Mar 2021) A Generalization of Transformer Networks to Graphs - [Video](https://youtu.be/h-_HNeBmaaU?t=231) - [Slides](https://drive.google.com/file/d/1Vnk0hcQFofHmSHpDEZERzQ5CeqEsrj2s/view) ## Academic Services, Program Committee Member, Reviewer - ACL Rolling Review (ARR), 2024 - AAAI Conference on Artificial Intelligence (AAAI), 2025, 2024 - Learning on Graphs Conference (LoG), 2025, 2024, 2023, 2022 - Neural Information Processing Systems (NeurIPS), 2025, 2024, 2023, 2022 - International Conference on Learning Representations (ICLR), 2026, 2025, 2024, 2023, 2022 ([Highlighted Reviewer](https://iclr.cc/Conferences/2022/Reviewers)) - IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024, 2023 - IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023 - IEEE International Conference on Robotics and Automation (ICRA), 2022 - AAAI Workshop on Graphs and More Complex Structures for Learning and Reasoning (GCLR), 2022 - Neural Networks, Elsevier, 2022, 2021 - MLSys Workshop on Graph Neural Networks and Systems (GNNSys), 2021 - ICML Workshop on Graph Representation Learning and Beyond (GRL+), 2020 - Multiple NeurIPS, ICLR and ICML Workshops on graphs and geometric learning domains, 2022-now ## Contact Email: vdwivedi [AT] cs.stanford.edu GitHub: https://github.com/vijaydwivedi75 Twitter: https://twitter.com/vijaypradwi LinkedIn: https://linkedin.com/in/vijay321/ Website: https://vijaydwivedi.com.np/