I am working as an Assistant Professor at IIT Madras, Zanzibar. My research focuses on the modeling and analysis of infectious diseases using a combination of physics-informed machine learning, deep learning, and graph neural networks (GNNs). We integrate mechanistic models with data-driven techniques to capture complex disease dynamics influenced by environmental and mobility-related factors. We also study the generalization capabilities of deep learning architectures, including neural ordinary differential equations (ODEs), to improve robustness in various tasks including disease forecasting. Additionally, we apply physics-informed techniques to optimize inventory management systems, enhancing resource allocation efficiency in dynamic supply chains.  

During my PhD, we developed advanced frameworks for age and size-structured population models, with applications in epidemiology and ecological systems. My approach integrates deterministic/stochastic partial differential equations (PDEs), and control theory with modern machine learning. By bridging classical mathematical methods with innovations like neural ODEs and physics-informed AI, we aim to advance predictive modeling of disease dynamics, operational systems, and intervention strategies. 

I have completed my Ph.D. from the School of Mathematical and Statistical Sciences, Indian Institute of Technology Mandi (IIT Mandi). I obtained my master's degree from the Indian Institute of Technology Ropar (IIT Ropar) in 2018 and received a certificate of merit for obtaining the highest CGPA in M.Sc Mathematics. In 2016, I completed my B.Sc (Hons.) from Himachal Pradesh University (HPU) and was awarded the first position overall for achieving the highest CGPA at Govt. College Bilaspur.