Vijay Prakash Dwivedi

Interests. Machine Learning, Deep Learning on Graphs

I am a PhD student in Machine Learning at Nanyang Technological University, Singapore being supervised by Prof. Luu Anh Tuan (NTU) and Prof. Xavier Bresson (NUS). My primary interest is in developing deep learning algorithms and architectures on graph-structured data and exploring their applications in computational science applications.

Before starting my PhD, I worked with Prof. Bresson as a Research Assistant in the same lab. I have a background in Computer Science and Engineering (B.Tech.) from MNNIT Allahabad where I explored the fields of Natural Language Processing and Multi-Modal Computing.

Education

Nanyang Technological University (NTU), Singapore Doctor of Philosophy (PhD), 2019-present
School of Computer Science and Engineering
Motilal Nehru National Institute of Technology (MNNIT), Allahabad Bachelor of Technology (BTech), 2014-2018
Department of Computer Science and Engineering

Research Experience

Sony Group Corporation, Tokyo, Japan Research Intern, Jun-Aug 2022
Project: 3D Visual Generation
Developed a deep learning prototype to generate 3D body meshes from single 2D image inputs through the use of non-local Graph Transformers which operates on a template mesh graph and input image features to combine both visual and structural features in the best possible manner.
Media & Interactive Computing Lab, NTU Singapore Research Assistant, Feb-Jul 2019
Project: Deep Learning on Graphs
Designed a novel convolutional neural network with neighbor nodes’ attention for graph datasets.
Francium Technologies Pvt Ltd, Chennai [blog] Solution Consultant, Dec 2018-Feb 2019
Project: Removal of Noise in Document Image Processing
Developed a Masked RCNN based model to remove noise (signatures/stamps/tags) for processing document images in automatic text retrieval
Language Technologies Research Center (LTRC), IIIT Hyderabad [code] Research Intern, May-Jul 2017
Project: Beyond Word2Vec - Embedding Words and Phrases in Same Space
Designed a deep learning algorithm to learn vector embeddings of multi-word units (phrases) by maximizing the similarity among word units of different sizes having the similar meaning.
CogBID Lab, University of Stirling Research Intern (Remote), May-Jul 2017
Project: Multimodal Deception Detection Using Deep Learning
Proposed a novel methodology to detect deceit in videos using deep neural networks (LSTM for text, CLSTM for visual and SVM classifier for audio inputs).

Publications (Google Scholar)

Long Range Graph Benchmark, arXiv preprint arXiv:2206.08164, 2022. Vijay Prakash Dwivedi, Ladislav Rampášek, Mikhail Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu and Dominique Beaini [code]
Recipe for a General, Powerful, Scalable Graph Transformer, arXiv preprint arXiv:2205.12454, 2022. Ladislav Rampášek, Mikhail Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf and Dominique Beaini [code]
Graph Neural Networks with Learnable Structural and Positional Representations, 10th International Conference on Learning Representations (ICLR), 2022. Vijay Prakash Dwivedi, Anh Tuan Luu, Thomas Laurent, Yoshua Bengio and Xavier Bresson [code]
Self-critical Learning of Influencing Factors for Trajectory Prediction using Gated Graph Convolutional Network, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021. Niraj Bhujel, Yau Wei Yun, Han Wang and Vijay Prakash Dwivedi
A Generalization of Transformer Networks to Graphs, AAAI'21 Workshop on Deep Learning on Graphs: Methods and Applications (DLG-AAAI'21), 2021. Vijay Prakash Dwivedi and Xavier Bresson [code]
Benchmarking Graph Neural Networks, arXiv preprint arXiv:2003.00982, 2020. Vijay Prakash Dwivedi, Chaitanya Joshi, Thomas Laurent, Yoshua Bengio and Xavier Bresson [code]
Beyond Word2Vec: Embedding Words and Phrases in Same Vector Space, Proceedings of the 14th International Conference on Natural Language Processing (ICON), 2017, Kolkata, India. Vijay Prakash Dwivedi and Manish Shrivastava [code]
Gender Classification of Blog Authors: With Feature Engineering and Deep Learning using LSTM Networks., Proceedings of the 9th International Conference on Advanced Computing (ICoAC), 2017, Chennai, India. Vijay Prakash Dwivedi, Saurav Jha, Deepak Kumar Singh and Ranvijay

Keynotes, Talks and Tutorials

ML on Graphs (MLoG) Workshop at the 16th ACM International WSDM Conference, Singapore, March 2023 Keynote: Transformers for Graph Structured Data
4th NAAMII Nepal Winter School in AI, Kathmandu, Nepal, May 2022 Introduction to GNNs
3rd NAAMII Nepal Winter School in AI, Kathmandu, Nepal, December 2021 Introduction to GNNs
LoGaG: Learning on Graphs and Geometry Reading Group, Virtual, November 2021 Graph Neural Networks with Learnable Structural and Positional Representations
[Video] [Slides]
4th National Workshop on Machine Learning and Data Science, Kathmandu, Nepal, September 2021 Introduction to GNNs and Application Prospects
The DECAL Lab, UC Davis, April 2021 Benchmarking Graph Neural Networks
NTU SCSE-GSC Student Lecture Series, March 2021 A Generalization of Transformer Networks to Graphs
[Video] [Slides]

Academic Services, Program Committee Member, Reviewer

AAAI Conference on Artificial Intelligence (AAAI), 2024
Learning on Graphs Conference (LoG), 2023, 2022
Neural Information Processing Systems (NeurIPS), 2023, 2022
International Conference on Learning Representations (ICLR), 2023, 2022. (Highlighted Reviewer)
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 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