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tbs1980/README.md

Hi, I'm Sreekumar

Scientist turned AI builder working at the intersection of machine learning, scientific computing, and real-world systems.

I come from a background in astrophysics and Bayesian inference, where I developed high-performance computational methods to analyse cosmological data from space telescopes. My research contributed to the discovery of three exoplanets through large-scale C++ simulations.

Today I focus on building robust, efficient AI systems that translate scientific ideas into practical tools. My work has ranged from Bayesian deep learning for financial forecasting to multi-modal machine learning platforms for real estate analytics and underwriting.

I enjoy working with small, ambitious teams exploring new applications of AI and building systems from first principles.


Current Exploration

⚡ Energy-efficient machine learning
🧠 Scientific machine learning and probabilistic models
🌍 AI for geospatial intelligence and remote sensing
⛏️ Mineral discovery using ML and satellite data
🔍 Efficient adaptations of foundation models


Technical Stack

Languages

  • Python
  • C++

Machine Learning

  • PyTorch
  • Scikit-learn
  • Probabilistic modelling

Scientific Computing

  • High Performance Computing (HPC)
  • Bayesian inference
  • Numerical simulation

Domains

  • Geospatial & remote sensing
  • Financial modelling
  • Real estate market intelligence

Selected Experience

Machine Learning Leadership — Real Estate AI
Led development of a multi-modal ML platform combining tabular, text, and imagery data to forecast property markets and support underwriting decisions.

Entrepreneurship — AI in Finance
Co-founded a machine learning hedge fund through Entrepreneur First, developing Bayesian deep learning models for financial forecasting.

Scientific Research — Astrophysics
Developed Bayesian statistical methods and HPC software for analysing cosmological datasets from major space telescope missions.


Fun Fact

🛰️ I once co-wrote a C++ simulation to model exoplanet orbits — and the work contributed to the discovery of three planets.


Let's Connect

I'm always interested in discussing ideas at the intersection of:

  • machine learning
  • science-inspired AI
  • geospatial intelligence
  • efficient and data-lean AI systems

If you're building something interesting in this space, I'd love to hear about it.

Popular repositories Loading

  1. NumericalIntegration NumericalIntegration Public

    A C++ header-only, precision-independent library for performing numerical integration

    C++ 88 10

  2. KernelDensityEstimation KernelDensityEstimation Public

    Kernel Density Estimation

    C++ 11 10

  3. Ellipsis Ellipsis Public

    A library for Hamiltonian sampling

    C 4

  4. CosmicCrossCorrelation CosmicCrossCorrelation Public

    A project to measure cross-correlations between various cosmological data

    Python 4 1

  5. asymmetricTreeCluster asymmetricTreeCluster Public

    A code for clustering analysis using asymmetric tree structure

    C++ 4

  6. Cat2Map Cat2Map Public

    A C++ code for convgerting a galaxy catalogue to a HELPixMap

    C++ 4