Backend developer and data science student. I build the systems behind community platforms, and outside of that I keep returning to problems where information is degraded or hard to reach — a language with almost no computational tooling, syllables with hidden structure.
I'm a final-year B.E. Computer Science (Data Science) student at RNS Institute of Technology, Bengaluru, currently in my 7th semester. Most of my time right now goes into an AI Engineer internship at Laneway, where I work on backend development for an AI-powered platform using Python, FastAPI, and PostgreSQL.
Outside of that, I keep coming back to problems where the useful signal is buried: a text classifier that has to separate real meaning from noise, a language — Kannada — with very little existing NLP tooling, and poetic meter that's structured but rarely modeled computationally.
I'm also rebuilding my DSA fundamentals from the ground up ahead of placement season, treating it the same way I treat everything else — incrementally, and honestly about what I don't know yet.
Contributing to backend development for an AI-powered platform, working across API design, database logic, and system integration.
A rule-based system that analyzes Kannada poetic meter (chandassu), classifying syllables into Laghu (short) and Guru (long) using Unicode-aware text processing — built for a language with almost no existing computational linguistics tooling.
Translates Kannada text to English via Google Translator, then classifies sentiment — Positive, Negative, or Neutral — by scoring polarity with TextBlob after tokenization and stop-word removal.