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Achievement: Pull Sharkx4Achievement: Pair Extraordinairex4Achievement: QuickdrawAchievement: YOLO

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nandanito/README.md
Nandan Joshi — physics → machine learning → quantum

Physicist by training, now working where machine intelligence, quantum computing and cryptography for digital assets meet. What ties them together for me is how information becomes structure, signal, and eventually knowledge.

Now

QMI Lab · the independent lab I run
Research on intelligence and learning across classical and quantum computation. Current work: hybrid quantum-classical Transformer fine-tuning, and cross-lingual transfer through romanization.

AstroLLM · building an LLM for astronomy
Retrieval-grounded, QLoRA-tuned on Qwen3, wired to NASA ADS, SIMBAD and the Exoplanet Archive. Evaluated on grounding, tool routing, abstention and teaching quality.

Confidential Digital Assets · privacy on public ledgers
What confidential-token systems actually hide, established by running them rather than reading their docs, with every claim traced to evidence. First study: Zeto on Paladin (EVM). An XRPL (XLS-96) counterpart is coming soon.

PQC · post-quantum cryptography
Implementing post-quantum schemes from their NIST standards, and explaining them along the way. First project: slh-dsa-zig, SLH-DSA (FIPS 205) in pure Zig, with a guide to how the scheme works.

Beyond the lab, I work across the wider quantum computing stack: algorithms and circuits, hybrid quantum-classical methods, simulators and hardware back-ends, and the developer tooling that connects them.

Also learning in public: array-thinking-to-q, from J to q/kdb+ with every example executed.

Background

  • Diplom Physik, Göttingen (2007). DFG-funded doctoral research in stellar astrophysics at the Institut für Astrophysik Göttingen: observing at ESO facilities in Chile, custom IDL pipelines for spectroscopic analysis.
  • Max Planck Institute for Dynamics and Self-Organization. Q-learning agents controlling simulated artificial muscles, with the biomechanics modeled through Lagrangian mechanics. Reinforcement learning from before the deep-RL era.
  • Publication: Reiners et al., A Catalog of Rotation and Activity in Early-M Stars. The Astronomical Journal 143, 93 (2012). ADS

Toolbox

Python PyTorch Hugging Face vLLM Unsloth PennyLane Qiskit Zig TypeScript PostgreSQL Astro

Elsewhere

nandan.me · qmilab.com · astrollm.org · LinkedIn · X

Popular repositories Loading

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  6. array-thinking-to-q array-thinking-to-q Public

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