I'm an engineering student working across AI/ML, computer vision, backend systems, and embedded technology. My focus is on taking real problems — not toy datasets — and building systems that actually hold up: explainable models, measured latency, and interfaces people can use.
My core technical anchor is a semiconductor wafer defect detection system, currently the subject of a patent application, which has shaped the direction of most of my subsequent project work and hackathon pitches.
BUILD · EXPLAIN · SHIP
C++ · Python · Java · React · JavaScript · Node.js
FastAPI · Tailwind CSS · PyTorch · Docker · ChromaDB
Deep learning system for semiconductor wafer defect classification, built with a focus on interpretability and deployability rather than raw accuracy alone.
- ResNet18 classification pipeline with focal loss, trained on the WM-811K dataset across eight defect classes
- Grad-CAM based explainability layered with geometric boundary validation and rule-based inference for more trustworthy predictions
- ~12ms CPU inference latency, making it viable for real-time / edge deployment
- Confidence scoring and an interactive prediction dashboard on a full-stack web interface
A 12-module AI-powered study platform designed to make self-directed learning interactive rather than passive — spanning an AI Teacher, PDF engine, quiz engine, flashcards, voice AI, and a placement-prep module.
- Built on React/Vite (frontend) and FastAPI (backend), with the Anthropic API and ChromaDB for retrieval
- OCR-powered question extraction and an image-to-explanation workflow
- Designed for offline-first, local AI assistance
An interactive personal portfolio showcasing my AI/ML, computer vision, and embedded systems work.
- Built with Vite + React, React Three Fiber, Framer Motion, and Tailwind CSS v4
- View it live →
I treat DSA as a standing practice, not a phase — breaking problems down, comparing approaches, and optimizing for both correctness and efficiency.
AI Agents · Deep Learning · Backend Development · System Design
Preparing for Smart India Hackathon 2026, building on the explainable-AI and defect-detection work above.
Open to conversations on AI, computer vision, systems design, or interesting problems worth building for.