About

Signal, mostly, in one form or another.

I'm an AI/ML engineer based in Mumbai. I came to machine learning by way of electronics and telecommunication — antennas, breadboards, signal chains — at Vishwakarma Institute of Information Technology, and the habit never quite left: I still think of most of what I build as a signal moving through a system, whether that's a live phone call, a pulse trace on someone's wrist, or a player's guess at a secret a language model is trying to keep. These days that mostly means production speech pipelines at Emitrr, agentic systems that reason over documents, and the occasional paper on models that have to explain themselves.

Education — B.Tech, Electronics & Telecommunication Engineering, Vishwakarma Institute of Information Technology, Pune. GPA 9.14. Dec 2021 – June 2025.
  • Top 3 of 500+ teams, Auto PCOS Open Hackathon (MisaHUB)
  • 52nd on Hugging Face Hub's Leaderboard, July 2023
  • Open-source contributions to ReX (explainable AI) and Gensim (NLP)
AI / LLM & GenAI
Transformer Architecture, LLMs, RAG, Agentic AI, Multi-Agent Systems (CrewAI, LangChain), Prompt Alignment, LLM-as-Judge Evaluation
Speech & Audio
STT (Deepgram), TTS (ElevenLabs), Streaming Audio, Endpoint Detection, PPG Signals
ML / DL Frameworks
Scikit-learn, TensorFlow, PyTorch, OpenCV, HuggingFace Transformers
Languages & Backend
Python, C++, SQL, Bash, Flask, FastAPI
Data & Infra
PostgreSQL, FAISS, Docker, Git, Weights & Biases, AWS, GCP, Linux

Research & publications

Non-invasive blood glucose estimation using a novel white-box model: an interpretable machine learning approach

Biomedical Signal Processing and Control, Elsevier Q1 — Jan 2025 · R² 0.921 (ensemble), 90% Zone A on the Clarke Error Grid

Gastrointestinal bleeding detection using YOLOv5

ICMIB 2024, Springer Lecture Notes — March 2024

What I tend to optimize for

Different problem classes reward different design trades. These are the lenses I keep coming back to.

Speech + operational systems

The real differentiator is not the model in isolation — it is how the full streaming pipeline handles latency, turn boundaries, and failure states while the call is still live.

Live GitHub pulse

Public profile numbers fetched client-side from GitHub.

Public repos
Stars
Followers
Following