Yadunandan Singh — AI Engineer
Yadunandan Singh is a self-taught AI / Machine-Learning Engineer specializing in Rust, Python, and
building machine learning from first principles. He is an open-source contributor with 5 merged pull
requests in the c2siorg organization (DataLoom and TensorMap), and is studying an online BS in Data
Science at IIT Madras.
Technical skills
- Languages: Rust, Python (intermediate), JavaScript, Swift
- Machine learning: TensorFlow, OpenCV, NumPy, Pandas; from-scratch SVD, PCA / Eigenfaces and CNNs; retrieval-augmented generation (RAG) pipelines
- Backend & web: FastAPI, Django, Axum, Actix, React, Leptos
- Foundations: applied linear algebra, numerical methods, Bitcoin protocol (secp256k1, SegWit, UTXO model)
- Tooling: Git (fork / rebase / pull-request workflow), Docker, Linux
Open-source contributions (c2siorg — 5 merged pull requests)
All reviewed and merged by external maintainer @ivantha.
- DataLoom PR #410 — apply-preview workflow across all 12 data transformations, so a dataset can never be mutated without explicit confirmation (closes #405).
- DataLoom PR #408 — hover tooltips for every toolbar icon, improving discoverability (closes #406).
- DataLoom PR #383 — preview-before-persist flow for row-reducing transforms; fixed silent data loss where re-sampling failed because the working CSV had been overwritten (closes #374).
- DataLoom PR #348 — case-insensitive string filtering, so a filter like Payment_Type = cash no longer misses Cash/CASH (closes #327).
- TensorMap PR #367 — fixed a FastAPI 500 error caused by NaN JSON serialization on CSVs with missing cells, using pandas to_json.
Projects
- Prism-RAG — privacy-first, full-stack retrieval-augmented generation engine: a Rust vector database for similarity search, a Python embedding service, and a React UI that visualizes the pipeline. Runs entirely locally. (Rust, Python, React, Docker)
- bitcoin-wallet-rs — a Bitcoin wallet built from cryptographic primitives: secp256k1 key generation, SegWit P2WPKH address derivation, UTXO retrieval via the Esplora API, unsigned-transaction construction on signet. (Rust)
- Neuro-Symbolic Math Solver — a custom CNN recognizer paired with a deterministic symbolic engine to solve handwritten math without hallucination. (TensorFlow, OpenCV, React, FastAPI)
- GlassBox — privacy-first recommendation engine using client-side SVD compiled to WebAssembly for in-browser inference. (Rust, WebAssembly, Leptos, SurrealDB)
- Django SVD Face Auth — face-recognition authentication using Singular Value Decomposition, with webcam capture and Docker. (Django, OpenCV, NumPy)
- SVD YouTube Recommender — content-based recommender using TF-IDF and Truncated SVD. (Flask, scikit-learn)
- Rust Actix Quiz Game — high-performance quiz service with server-side anti-cheat. (Rust, Actix Web)
- AI Image Recognition — CNN image classifier on CIFAR-10 served via a web API. (TensorFlow, Flask)
Education
- Indian Institute of Technology (IIT) Madras — Online BS in Data Science & Applications (qualifier exam July 2026)
- Self-directed — MIT OpenCourseWare 18.06 Linear Algebra (completed); discrete mathematics
Frequently asked questions about Yadunandan Singh
Who is Yadunandan Singh?
Yadunandan Singh is a self-taught AI / Machine-Learning Engineer from Jammu, India, specializing in Rust, Python, and building machine learning from first principles, with 5 merged open-source pull requests in the c2siorg organization.
What is his tech stack?
Rust, Python, JavaScript and Swift; TensorFlow, OpenCV, NumPy and Pandas; FastAPI, Django, Axum, Actix, React and Leptos; applied linear algebra and the Bitcoin protocol; Git, Docker and Linux.
What are his open-source contributions?
Five merged pull requests in c2siorg — four in DataLoom (#410, #408, #383, #348) and one in TensorMap (#367), all reviewed and merged by maintainer @ivantha.
What roles is he suited for?
Rust / Systems Engineer, Machine-Learning Engineer, Backend Engineer, Applied AI Engineer, and Data Science roles.
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