Doctoral researcher at the UGC-DAE Consortium for Scientific Research (Mumbai),
working at the intersection of Condensed Matter Physics and
Computational Science.
I cover the full research stack — from designing cryogenic hardware
and automating data acquisition to building simulation models and
AI-driven analysis tools.
I am a PhD student in Condensed Matter Physics specialising in Materials Science and Scientific Computing. My work aims to modernise experimental physics by developing open-source tools that seamlessly connect lab hardware, data acquisition, and theoretical modelling.
- Open to: Postdoctoral positions in Condensed Matter or Computational Physics.
- Code: Primary repositories on GitHub; mirrored to GitLab periodically.
- Contact:
prathameshnium[at]duck[.]com
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Open hardware reference design for a modular cryogenic platform optimised for high-impedance transport, pyroelectric, and magnetodielectric characterisation in PPMS (14 T) environments. |
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A privacy-first AI toolkit built on local LLMs via Ollama. Features Orochimaru, a RAG-powered assistant for analysing academic PDFs and generating structured literature reviews — entirely offline. |
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| Repository | Focus | Stack |
|---|---|---|
| Physics-Simulation-Toolkit | Ising model, magnetic ordering, dielectric relaxation | Python, Jupyter |
| Solid-State-Calculators | Arrhenius plots, Mott-VRH transport, activation energy | Python, SciPy |
| TupperTransformer | Interactive bitmap engine for Tupper's self-referential formula | JavaScript |
| Python-for-OriginPro | Automated plotting and data management in OriginLab | Pandas, OriginC |
- Experimental: Low-temperature transport · Dielectric spectroscopy · Magnetometry
- Computing: Instrument control (PyVISA) · Data pipelines · Simulation · Local AI (RAG)


