ProtoCF: Prototypical Collaborative Filtering for Few-shot Recommendation
Aravind Sankar, Junting Wang, Adit Krishnan, Hari Sundaram, RecSys 2021: Fifteenth ACM Conference on Recommender Systems, Virtual Event, Brazil, September 22-26, 2020 PDF
Education
- Ph.D in Computer Science, University of Illinois, Urbana-Champaign, 2016-2021.
- M.Tech. in Computer Science and Engineering, Indian Institute of Technology Madras, 2016
- B.Tech. in Computer Science and Engineering, Indian Institute of Technology Madras, 2016
Work experience
- Present: Research Scientist, Core Data Science
- Meta Research, Menlo Park CA.
- Graph Representation Learning for user understanding and modeling.
- Summer 2020: Research Intern, Computational Social Science Team.
- Snap Research, Santa Monica, CA.
- Graph Neural Networks for friend recommendations in large-scale social platforms.
- Supervisor: Dr. Neil Shah.
- Summer 2019: Research Intern, Recommendations Team.
- Visa Research, Palo Alto, CA.
- Neural framework to make recommendations for ephemeral groups of users.
- Mentor: Dr. Yanhong Wu.
- Summer 2018: Research Intern, Risk Modeling Team.
- Visa Research, Palo Alto, CA.
- Representation learning to model user behavior in temporally evolving networks.
- Mentor: Dr. Yanhong Wu and Dr. Liang Gou .
- Summer 2014: Research Intern, Digital Marketing Team.
- Adobe Research Labs, Bengaluru, India.
- Similarity Learning for multi-channel product recommendations.
- Mentor: Dr. Iftikhar Burhanuddin .
Skills
- Programming Languages: Python, Java, C/C++, HTML and CSS
- Statistical Analysis and Machine Learning: PyTorch, TensorFlow, Keras, and Matlab.
- Miscellaneous: LaTex, Django and SQL.
Publications
Graph Neural Networks for Friend Ranking in Large-scale Social Platforms
Aravind Sankar, Yozen Liu, Jun Yu, Neil Shah, Proceedings of The Web Conference 2021, WWW 2021, Ljubljana, Slovenia, April 2021 PDF
Beyond Localized Graph Neural Networks: An Attributed Motif Regularization Framework
Aravind Sankar, Junting Wang, Adit Krishnan, Hari Sundaram, 2020 IEEE International Conference on Data Mining (ICDM), ICDM 2020, November 17-20, 2020 PDF
GroupIM: A Mutual Information Maximization Framework for Neural Group Recommendation
Aravind Sankar, Yanhong Wu, Yuhang Wu, Wei Zhang, Hao Yang, Hari Sundaram, International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020, July 25-30, 2020 PDF
Inf-VAE: A Variational Autoencoder Framework to Integrate Homophily and Influence in Diffusion Prediction
Aravind Sankar, Xinyang Zhang, Adit Krishnan, Jiawei Han, International Conference on Web Search and Data Mining, WSDM 2020, Houston, TX, February 3-7, 2020 PDF
DySAT: Deep Neural Representation Learning on Dynamic Graphs via Self-Attention Networks
Aravind Sankar, Yanhong Wu, Liang Gou, Wei Zhang, Hao Yang, International Conference on Web Search and Data Mining, WSDM 2020, Houston, TX, February 3-7, 2020 PDF
RASE: Relationship Aware Social Embedding
Aravind Sankar, Adit Krishnan, Zongjian He, Carl Yang, International Joint Conference on Neural Networks, IJCNN 2019 Budapest, Hungary, July 14-19, 2019 PDF
Meta-GNN: Metagraph Neural Network for Semi-supervised learning in Attributed Heterogeneous Information Networks
Aravind Sankar, Xinyang Zhang, Kevin Chang, IEEE/ACM 2019 International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019, Vancouver, Canada, August 27-30, 2019 PDF
Discovering Maximal Motif Cliques in Large Heterogeneous Information Networks
Jiafeng Hu, Reynold Cheng, Kevin Chang, Aravind Sankar, Yixiang Fang, Brian Lam, 35th IEEE International Conference on Data Engineering, ICDE 2019, Macao, China, April 8-11, 2019 PDF
An Adversarial Approach to Improve Long-Tail Performance in Neural Collaborative Filtering
Adit Krishnan, Ashish Sharma, Aravind Sankar, Hari Sundaram, Proceedings of the 27th ACM International Conference on Information and Knowledge Management, CIKM 2018, Torino, Italy, October 22-26, 2018 PDF
Unsupervised Concept Categorization and Extraction from Scientific Document Titles
Adit Krishnan, Aravind Sankar, Shi Zhi, Jiawei Han, Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, CIKM 2017, Singapore, November 06 - 10, 2017 PDF
Predicting novel metabolic pathways through subgraph mining
Aravind Sankar, Sayan Ranu, Karthik Raman, Bioinformatics PDF
Improved MHP Analysis
Aravind Sankar, Soham Chakraborty, V. Nandivada, Proceedings of the 25th International Conference on Compiler Construction, CC 2016, Barcelona, Spain, March 12-18, 2016 PDF
Similarity Learning for Product Recommendation and Scoring Using Multi-channel Data
Iftikhar Burhanuddin, Payal Bajaj, Sumit Shekhar, Dipayan Mukherjee, Ashish Raj, Aravind Sankar , IEEE International Conference on Data Mining Workshop, ICDMW 2015, Atlantic City, NJ, USA, November 14-17, 2015 PDF
Teaching
Computational Advertising (Teaching Assistant)
University of Illinois, Urbana-Champaign, Computer Science
Social and Information Networks (Teaching Assistant)
University of Illinois, Urbana-Champaign, Computer Science
Database Systems (Teaching Assistant)
University of Illinois, Urbana-Champaign, Computer Science
Advanced Data Management (Teaching Assistant)
University of Illinois, Urbana-Champaign, Computer Science
Data Mining (Teaching Assistant)
Indian Institute of Technology, Madras, Computer Science and Engineering
Searching and Indexing in Large Datasets (Teaching Assistant)
Indian Institute of Technology, Madras, Computer Science and Engineering
Service and Leadership
- Program Committee Member, Network Modeling, Learning and Analysis (NMLA), WorldCIST2020 Workshop, 2020.
- Program Committee Member, International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020.
- Invited reviewer for Neurocomputing, Machine Learning (MACH), IEEE Transactions on Neural Networks and Learning Systems Journal (TNNLS), and ACM Transactions on Information Systems (TOIS) journals.
- Subreviewer, The Web Conference, WWW 2020 and 2021.