About me
I’m a second-year Ph.D. scholar at McGill University and Mila - Quebec AI Institute, where Prof. William Hamilton advises me. I completed my M.S by Research (Thesis) at the Indian Institute of Technology Madras (IIT M) under the guidance of Prof. Balaraman Ravindran. I have 5 years of experience as a research staff working at IIT Madras, where I was associated with the Robert Bosch Centre for Data Sciences and AI (RBCDSAI) and RISE Interactive Intelligence Lab.
My research interests lie in the broad areas of Machine Learning and Complex Networks, especially at their intersection, where I design Deep Neural Network models for relational representation and reasoning tasks in irregularly structured domains.
Updates
2021
- Our work on EGO-GNNs: Exploiting EGO Structures in Graph Neural Networks by D Sandfelder, P Vijayan and W L Hamilton will appear in the Proceedings of the
International Conference on Acoustics, Speech, and Signal Processing, ICASSP'21.
2020
- Our work on Understanding Dynamic Scenes using Graph Convolution Networks by S Mylavarapu, M Sandhu, P Vijayan, M Krishna, B Ravindran, and A Namboodiri is available in the Proceedings of the
International Conference on Intelligent Robots and Systems, IROS'20.Paper | Video | Code - Our Work on On Incorporating Structural Information to Improve Dialogue Response Generation by
N Moghe, P Vijayan, B Ravindran, and M Khapra is available in the Proceedings of
NLP for Conversational AI workshop, ACL'20.Paper | Code - Our work on Influence Maximization in Unknown Social Networks: Learning Policies for Effective Graph Sampling by H Kamarthi, P Vijayan, B Wilder, B Ravindran, and M Tambe is available in the Proceedings of the
International Conference on Autonomous Agents and Multiagent Systems, AAMAS'20.[Nominated for Best Paper Award] Paper | Code - Our work on A Unified Non-Negative Matrix Factorization Framework for Semi-Supervised Learning on Graphs by A Mitra, P Vijayan, S Parthasarathy, and B Ravindran is available in the Proceedings of
SIAM International Conference on Data Mining, SDM'20.Paper | Code | Supplement - Our work on Towards Accurate Vehicle Behaviour Classification With Multi-Relational Graph Convolutional Networks by S Mylavarapu, M Sandhu, P Vijayan, M Krishna, B Ravindran, and A Namboodiri will appear in the Proceedings of
IEEE Intelligent Vehicles Symposium, IV'20.Paper | Code
Service
- Program Commitee Member: EMNLP (2021), SIAM SDM (2021), NAACL-HLT (2021), GCLR Workshop AAAI (2021), ADCOM (2018), CODS-COMAD (2018)
- Reviewer: NeurIPS (2021), ICLR (2021, 2020), DMKD Journal (2019), ACL(2018)
Teaching Assistant
- COMP596-001: Network Science (Fall’20)
- COMP598-001: Introduction to Data Science (Fall’20)
- COMP767-001: Graph Representation Learning (Winter’20)
Courses
McGill University
- COMP767-001: Reinforcement Learning
- COMP550-001: Natural Language Processing
- COMP767-002: Probabilistic Graphical Models
Indian Institute of Technology Madras
- CS5011: Introduction to Machine Learning
- CS6012: Social Network Analysis
- CS7015: Deep Learning
- CS6720: Data Mining
- CS6310: Deep Learning for Computer Vision
- CH5440: Multivariate Data Analysis