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Exploring math, algorithms, and clean code
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Exploring math, algorithms, and clean code

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abhrankan/README.md

Abhrankan Chakrabarti

On the intersection of number theory and computation


About

I work at the intersection of mathematical structure and computation.

My interests include number theory, numerical methods, and the design of efficient algorithms for mathematically structured problems. I focus on translating theoretical insight into precise, efficient, and computationally elegant implementations.

📄 Download Resume


Research Focus

  • Algorithmic Number Theory
  • Numerical Methods & High-Precision Computation
  • Structure-driven Algorithm Design

Selected Work

  • Catalan π Algorithm
    A novel computational framework for approximating π based on Catalan number structures, emphasizing deterministic convergence and fixed-point arithmetic efficiency.

  • Almost Isosceles Pythagorean Triples Optimizer
    An optimized recurrence-based method for generating structured Diophantine triples with near-isosceles properties.

  • Complex Calculator
    Implementation of complex arithmetic systems in C++ and Python with a focus on precision and usability.

  • Interactive Matrix Calculator
    Computational tool for matrix operations with an emphasis on clarity and algorithmic correctness.

  • LlamaInteract
    Local large language model interaction system built using llama.cpp for efficient on-device inference.

  • Winternship 2025 Case Studies
    Full MERN stack training — TypeScript, React (Vite), MongoDB (ACID transactions), and Express.js REST APIs with MVC architecture.


Publications / Notes


Tools & Environment

  • Languages: C++, Python, Java, TypeScript, JavaScript
  • Web & Backend: React (Vite), Node.js, Express.js, MongoDB
  • AI / ML: NumPy, Pandas, scikit-learn, Gemini Pro Vision, DALL-E 3, llama.cpp
  • Systems: Linux, Git
  • Editor: VS Code

Contact


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