​I have recently completed my Integrated M.Sc. in Mathematics at Veer Surendra Sai University of Technology (VSSUT), graduating with a 9.44 CGPA. My academic and professional journey is driven by a deep fascination with Machine Learning, Data Science, Applied Mathematics, and Explainable AI (XAI).

​Throughout my studies, I have actively pursued applied research, resulting in multiple papers currently under review for international journals. My work primarily leverages Physics-Informed Neural Networks (PINNs) and Explainable Machine Learning to solve complex, real-world problems. This includes developing predictive frameworks for healthcare risks like Alzheimer's and heart disease, as well as modeling real-time battery prognostics and computational fluid dynamics.

​I have continuously strengthened my analytical and technical capabilities through research internships at the National Institute of Science Education and Research (NISER), Amity University, and the Advanced Mathematical Innovation Center for Artificial Intelligence and Scientific Computing (AMICAISC). Additionally, I have gained practical, industry-facing experience through data analytics and visualization job simulations with Deloitte Australia and Tata.

​Beyond independent research, I am deeply engaged in the academic community. I have proudly served on the organizing committees and presented my research at international conferences, including ICPAM-DS 2026 and ICAMDS 2026.

​Currently, I am exploring opportunities to either tackle complex enterprise data challenges in the industry or pursue a PhD to further my research in Machine Learning and Optimization analysis.