DTU CSE / Applied ML

Applied ML. Built for use.

I work at the intersection of ML, retrieval, NLP, and usable software: systems that understand messy inputs and turn them into decisions, guidance, or action.

Explore Work Resume

Selected Projects

Project case files.

Priority 01 GitHub

Sororia

A women empowerment platform combining safety tools, scheme awareness, community forums, petitions, and SororAI guidance.

Problem

Information, safety, and support are scattered when they need to be immediate.

System

Built a Flutter platform with real-time news, secure route planning, SOS tools, forums, and an AI assistant for rights and complaint drafting.

Stack

Flutter · Gemini · Firebase · Selenium

Internship

MCD Internship.

Jul 2025 - Aug 2025

Data Science and Software Engineering Intern

Led analysis of Delhi house-tax data and developed anomaly signals to help identify records worth closer review.

Audited the house-tax payment website, documented reliability and payment-flow issues, and proposed actionable fixes.

Built the MACP scheme portal with Node.js, Express, Prisma, and PostgreSQL to digitize an internal employee process.

Working Style

Practical, measured, and user-aware.

Start with the decision.

A model is only useful when it changes what someone can see, prioritize, automate, or understand.

Respect the input.

Most quality gains come before inference: cleaning, chunking, metadata, retrieval design, and failure handling.

Ship the interface around it.

The best technical work still needs a clear surface where people can trust it, correct it, and use it repeatedly.

Open Channel

ML, RAG, data products, internships.

I am open to opportunities where machine learning is tied to a real workflow, a real user, and measurable improvement.

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