Dual-degree student pursuing B.Tech Computer Science (AI/ML) at MIT Manipal (CGPA: 8.70) and B.Sc Data Science at IIT Madras (CGPA: 8.1). Finalist at Adobe Hackathon with specialization in computer vision, 3D object recognition, and production ML systems. Former NDA cadet (AIR-254, 0.07% acceptance rate).

Production-ready document processing pipeline with persona-aware content filtering

• Custom heading extraction: 92% accuracy across diverse PDF structures
• 768-dimensional semantic embeddings for contextual understanding
• Sub-10-second processing for 50-page documents
• Fully offline architecture with no external API dependencies

Deep learning on ModelNet40 dataset for real-world 3D recognition tasks

• 85%+ classification accuracy across 40 object categories
• Spatial Transformer Networks for rotation-invariant recognition
• Training on 12,000+ point cloud samples
• Applications: Autonomous systems, robotics, AR/VR

Multi-model computer vision system for medical applications

• Weighted ensemble of specialized CNN architectures
• Real-time inference with clinical-grade accuracy
• Custom data augmentation and preprocessing pipelines
• Interpretable predictions for healthcare deployment

Keystroke dynamics-based user verification system

• Pure ML approach without rule-based heuristics
• Temporal pattern recognition in typing behavior
• Continuous authentication with adaptive learning
• Low-latency prediction suitable for production

AIML Domain Lead | MIT ACM Student Chapter

• Leading technical initiatives with 10+ ML projects in production
• Organizing hands-on workshops and hackathons
• Mentoring students on ML implementation and deployment

• Adobe Hackathon: Advanced to finalist round among nationwide participants
• NDA Selection: AIR-254 with 0.07% acceptance rate
• Research: Summer internship at IIT Jodhpur on ML applications
• Academic: Consistent 8.5+ CGPA across dual degree programs
• Leadership: 40% participation growth in ACM chapter events

• Computer Vision and 3D Deep Learning
• Production ML Systems and MLOps
• Real-time Inference and Optimization
• Distributed Computing with Spark
• Open Source Contributions

Currently seeking: ML Engineering roles, Computer Vision positions, AI Research opportunities