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ayushdwivedi-stack/README.md

B.Tech · Galgotias College of Engineering and Technology





About

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


Tech Stack

C++ · Python · Java · React · JavaScript · Node.js

FastAPI · Tailwind CSS · PyTorch · Docker · ChromaDB


Featured Work

01 — Wafer Defect Detection System (Patent-pending)

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

02 — AI Study Assistant

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

03 — Personal Developer Portfolio

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 →

DSA & Problem Solving

I treat DSA as a standing practice, not a phase — breaking problems down, comparing approaches, and optimizing for both correctness and efficiency.


Currently Exploring

AI Agents · Deep Learning · Backend Development · System Design



Preparing for Smart India Hackathon 2026, building on the explainable-AI and defect-detection work above.


Let's Connect

Open to conversations on AI, computer vision, systems design, or interesting problems worth building for.


Portfolio · LinkedIn · Email · GitHub





Building with curiosity. Learning with consistency.

Pinned Loading

  1. wafer-defect-detection wafer-defect-detection Public

    “An AI-powered wafer defect detection system using deep learning to automatically identify and classify semiconductor manufacturing defects for improved quality control.”

    Python 1