"Advancing the frontiers of Privacy-Preserving AI through Federated Learning and Computer Vision."

I am an Integrated M.Tech student in Artificial Intelligence at VIT Bhopal University with a CGPA of 8.61/10. My work focuses on building robust, privacy-centric machine learning architectures, particularly in Federated Learning and Multi-Modal Data Fusion. As a published researcher, I bridge the gap between academic theory and real-world deployment in disaster management and agricultural technology.

• Developed a Heterogeneous Federated Learning (HeteroFL) framework.
• Fused Satellite Imagery, Rainfall Data, and Water Levels for flood prediction.
• Publication: Accepted at the ASSIC Conference '26.

• Engineered a privacy-preserving FL architecture for TIHAN (IIT Hyderabad).
• Created the first-ever annotated dataset for Mahua crops and fine-tuned ResNet models.

• Designed a Graph Neural Network (GNN) to identify high-velocity transaction anomalies.
• Optimized the privacy-utility tradeoff against industry baselines like GCN and GraphSAGE.

• Cloud Expertise: AWS Certified (Cloud & ML Specialization) and NPTEL Cloud Computing.
• Specialized Training: Applied Machine Learning in Python (Coursera) and IT Support (Google).
• Leadership: Led a National Service Scheme (NSS) team during a large-scale Tree Plantation Drive.

“Coding with a conscience, building with privacy.”