
Gradient Atlas
01Interactive ML course
Learn ML by building it: 24 chapters, 512 flashcards, NumPy from scratch.
Hi, I'm
A data scientist with a background in electronics and communication engineering. I build machine learning, signal processing and LLM tools, and I ship each one as something you can open and use.
01 Selected work
Hover a project to preview it · Click to open itTap a project to open it

01Interactive ML course
Learn ML by building it: 24 chapters, 512 flashcards, NumPy from scratch.

02Physics research with SINP
Neutron vs gamma-ray signals: 512-D STFT features, up to 100% accuracy.

03Data analytics dashboard
50,000 electric vehicles, every figure computed live from the raw CSV.

04LLM agent for CAD drawings
Ask building plans anything; 20 tools measure every number from the DXF.

05Retrieval-augmented Q&A
Upload a PDF; answers come only from its top 4 passages. No servers.
Computer vision, robotics and AutoML experiments, plus hackathon work.
All repositoriesJunior Data ScientistCalsoft
Clean and analyse real-world datasets end to end, and build the Power BI dashboards product teams decide with.
AI/ML InternCalsoft
Built ML, deep learning and LLM solutions in Python, and validated models and dashboards before release.
Thesis ResearcherSaha Institute of Nuclear Physics
Neutron/gamma classification for a dark-matter detector: 512-D STFT features from 200 real events, SVM from scratch, up to 100% accuracy. See the project
Neutron vs gamma-ray acoustic signals, with MLSINP
Writing up the thesis results on superheated liquid detectors for publication.
M.Tech, Robotics & Artificial IntelligenceIndian Institute of Technology Guwahati
Master of Technology in robotics and artificial intelligence, studied alongside my role at Calsoft.
B.Tech, Electronics & Communication EngineeringRCC Institute of Information Technology
Bachelor of Technology. The signals and systems foundation behind my signal-processing work.
Higher Secondary, PCMBBethune Collegiate School
Physics, chemistry, mathematics and biology.
SecondaryBethune Collegiate School
Secondary schooling, completed in 2020.
Six areas I work across. Hover or tap a panel to open it.
Classical ML from scratch, SVMs, logistic regression, AutoML pipelines and careful model validation.
YOLOv8 detection, OCR, stereo depth estimation, and image and video pipelines.
RAG systems, tool calling, and LLM-assisted feature selection and error correction.
STFT feature extraction, pulse localisation and physics-grade classification.
Cleaning messy real-world data, exploratory analysis and dashboards that drive decisions.
Interactive web dashboards, in-browser ML, Flask apps, and deployments on Netlify and Vercel.
05 Say hello
Open to roles, research collaborations and interesting problems in machine learning, computer vision and signal processing. Email is the quickest way to reach me.

Interactive ML course
Learn ML by building it, not memorising it.
24 chapters of classical machine learning as an explorable map, study route, flashcards and a Python-style console. You write each algorithm in plain NumPy, then check it against scikit-learn.

Physics research with SINP
A neutron's acoustic signature versus a gamma ray's.
My thesis work for a superheated-liquid dark-matter detector: pulse localisation, STFT features, and logistic regression and SVM written from scratch. Drop in a waveform and it classifies it in your browser.

Data analytics dashboard
Washington State's electric vehicles, in one dashboard.
Every number, chart and written insight is calculated in the browser from the raw CSV, so a newer data export updates the whole site with no code changes.

LLM agent for CAD drawings
Measured, not guessed.
Ask building plans, distribution boards and circuits anything in plain English. Deterministic tools measure every number from the DXF, and hybrid search cites the exact spec clause for pass or fail checks.

Retrieval-augmented Q&A
Ask the document, not the internet.
Upload a PDF and get answers grounded only in its most relevant passages. Parsing happens in the browser, and embeddings live in Netlify Blobs, so there's no external vector database.