
Research Projects

Network Analysis of Neuro-Cognitive Processes: Studying McGurk Effect using EEG Data
Advisors: Dr. Arpan Banerjee, Dr. Ganesh Bagler, Dr. Dipanjan Roy [Link]
The research work involved understanding multi-sensory perception involving auditory and visual cues using the McGurk effect. My focus in this research was to understand the network properties of the brain using EEG data obtained from multiple subjects.

Network Analysis of Food-Disease Associations
Advisor: Dr. Ganesh Bagler [Link]
The focus of this research was to use clustering analysis to infer how different food and disease categories relate to each other. We created signed bipartite graphs using mined food-disease associations data and found clusters using Bi-Louvain algorithm.

BCQ4DCA: Budget Constrained Deep Q-Network for Dynamic Campaign Allocation in Computational Advertising
TCS Research and Innovation [Link]
We developed a deep reinforcement learning model for dynamic optimization of budget-constrained campaign allocation.
Publications
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M. Malik, G. Gupta, L. Vig, and G. Shroff, BCQ4DCA: Budget Constrained Deep Q-Network for Dynamic Campaign Allocation in Computational Advertising, IEEE International Joint Conference on Neural Networks, 2021 (accepted).
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Y. Rauthan, V. Singh, R. Agrawal, S. Kadlay, N. Pedanekar, S. Karande, M. Malik, and I. Tariang, Avoid Crowding in the Battlefield: Semantic Placement of Social Messages in Entertainment Programs, International Workshop on AI for Smart TV Content Production, Access and Delivery (AI4TV '20)