AI/ML Research-Focused Engineer · B.Tech IT '28 · Building data-driven systems for FinTech & Risk Intelligence
Third-year IT undergraduate focused on applied AI/ML, with a specific interest in FinTech risk systems — fraud detection, anomaly detection, and financial decision intelligence. Background spans full-stack engineering (MERN) to ML systems built end-to-end: feature engineering, ensemble modeling, and deployment-minded design.
Currently:
- 🔭 Sharpening ML fundamentals and research depth for graduate study and high-impact AI/ML research roles
- 🧠 Exploring the intersection of engineering and finance — long-term goal of building a finance-focused tech venture
- 🏆 1st place, MIT ADT AI Grand Challenge 2026 · Top 5%, IGNISIA '26 · Top 6, XENIA Hackathon 2026
- 🎓 Leadership: Director, Renascent Mirai Foundation · President, IT Tech Club MMCOE · Webmaster, IEEE Student Branch MMCOE
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Insurance fraud detection system XGBoost-based classification pipeline for identifying fraudulent insurance claims, with feature engineering tailored to claim-pattern anomalies and class-imbalance handling.
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On-device cognitive load predictor Lightweight ML model designed to estimate real-time cognitive load from on-device signals, optimized for low-latency inference without server dependency.
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AI-driven routing system Intelligent routing engine that applies AI-based decision logic to optimize path/route selection over conventional heuristic approaches.
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Personal site for grad & recruiter outreach Built with React, TypeScript, and Tailwind — a personal site designed around clarity, performance, and a strong first impression.
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ML / Data Science
Full-Stack Development
Languages
Tools
