I am broadly interested in machine learning, with specific interests in deep multi-task learning, learning with temporal point processes, and network representation learning. I am also interested in scalable and distributed machine learning, e.g. sketches and coresets. I have applied these techniques on problems in information extraction, computer vision, natural language processing, web and e-commerce, computational advertising, bioinformatics, online social networks.
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Stark: Fast and Scalable Strassen's Matrix Multiplication using Apache Spark Misra C., Bhattacharya S. , Ghosh S. K. By IEEE Transactions on Big Data 1-12 (2020)
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Multi-criteria online frame-subset selection for autonomous vehicle videos. Das S., Mandal S. , Bhoyar A. , Bharde M. , Ganguly N. , Bhattacharya S. , Bhattacharya S. By Pattern Recognition Letters 133 349-355 (2020)
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Learning Linear Influence Models in Social Networks from Transient Opinion Dynamics De A., Bhattacharya S. , Bhattacharya P. , Ganguly N. , Chakrabarti S. By ACM Transactions on the Web (TWEB) 13 1-33 (2019)
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Explaining Perceived Emotion Predictions in Music: An Attentive Approach Chaki S., Doshi P. , Bhattacharya S. , Patnaik P. By ISMIR Conference - (2020)
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Scalable Backdoor Detection in Neural Networks. Harikumar H., Lee V. , Rana S. , Bhattacharya S. , Gupta S. , Venkatesh S. By ECML PKDD - (2020)
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Demarcating Endogenous and Exogenous Opinion Diffusion Process on Social Networks De A., Bhattacharya S. , Ganguly N. By The Web Conference 549-558 (2018)
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Shaping Opinion Dynamics in Social Networks De A., Bhattacharya S. , Ganguly N. By International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 1336-1344 (2018)
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Task-Specific Representation Learning for Web-scale Entity Disambiguation. Kar R., Reddy S. , Bhattacharya S. , Dasgupta A. , Chakrabarti S. By AAAI conference on Artificial Intelligence - (2018)
Principal Investigator
- AI/ML Techniques for Online Shopping (Parent Project)
- AI/ML Techniques for Online Shopping (Sub Project II)
- Data-centric Trusted AI
- Learning Representations from Network Data
Co-Principal Investigator
- Google Unrestricted Fund for Social Computing GOOGLE INDIA PRIVATE LIMTED
- Property Preserving Data Gradation for Autonomous Vehicle Data HEWLETT-PACKARD (INDIA) SOFTWARE OPERATION PRIVATE LIMITED
- Understanding and Predicting Opinion Dynamics In Collective Environment Using Deep Network Representation CISCO University Research Program Fund
- Unrestricted grant for research in social networks and user-generated content Dr. M Chelliah, Head, Academic Relations, Yahoo India R & D
- Unrestricted Travel Grant Various Institutes/Organisations
- Virtual Labs (Phase III) Ministry of Human Resource Development
- VIRTUAL LABS PROJECT(PHASE-III EXTENDED) MHRD, Department of Higher Education, NMEICT, New Delhi
Ph. D. Students
Jyothi Pulikanti
Area of Research: Machine Learning, Information Retrival
Kiran Purohit
Area of Research: Machine Learning, Computer Vision
Paramita Koley
Area of Research: Machine Learning, Network Science
Rajdeep Mukherjee
Area of Research: Web Mining
Sanga Chaki
Area of Research: Computational Musicology
Saurabh Singh
Area of Research: Scalable Machine Learning
Soumi Das
Area of Research: Machine Learning, Networks
MS Students
Saptarshi Mondal
Area of Research: Machine Learning, Information Retrieval
Shubhadip Nag
Area of Research: Machine Learning, Information Retrieval