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  • Wolfram Research
  • Austin

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BhuvaneshBhatt/README.md

👋 Hello, I'm Bhuvanesh

  • Thanks for popping by! I'm a software engineer at Wolfram Research. I test Mathematica's functionality for machine learning, symbolic computation, special functions and data paclets (Mathematica's binary-encoded curated updatable datasets). I previously also tested the functionality for geometry and graph theory.
  • I used to code for TI calculators in my college years.
  • I am a proactive self-starter and largely self-motivated but I really enjoy working as part of a team. I am logical, creative and good at problem-solving, and I quickly pick up knowledge from diverse fields as relevant to a project.
  • I welcome you to join me on my learning journey! Feel free to follow me on Medium or on LinkedIn to stay in the loop of exciting and insightful content.
  • Do give my data science portfolio a look, and don't hesitate to contact me for a discussion on topics common to both of us!

"The task is not so much to see what no one has yet seen, but rather to think what no one has yet thought, about that which everyone sees." – Erwin Schrödinger

Project Count GitHub stars

Skills

My skills include:

  • computational math (symbolic and numeric),
  • special functions (I implemented harmonic polylogarithms and multiple zeta values for Mathematica),
  • probability and statistics (I implemented some statistical distributions and Markov processes for Mathematica),
  • data science (data analysis, machine learning),
  • data structures and algorithms,
  • functional and object-oriented programming,
  • and physics.

Hobbies and Interests

My hobbies and interests include playing board games, reading, listening to music, practising music, photography, hiking, biking, camping, stargazing. In the past, I've volunteered for Austin Wildlife Rescue and Refugee Services of Texas; both causes are very dear to me.

How to reach me

 

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  1. DataScienceReview DataScienceReview Public

    A review of data science I did in March and April 2025, including regression, bootstrapping, dimension reduction, anomaly detection, the EM algorithm, priors, MCMC and Variational Inference.

    Jupyter Notebook 1

  2. SpecialFunctions SpecialFunctions Public

    Implementations of various special functions, including multiple polylogarithms

    Jupyter Notebook 1

  3. SymbolicMath SymbolicMath Public

    Symbolic math computation

    Jupyter Notebook 1