[ Computational Researcher ]

Satyam
Sangeet

I build models of living systems: neural networks that read biological data, simulations of how viruses mutate and drugs bind, and mathematical models of the body's 24-hour clock.

[ Machine learning · live MLP ] FIG-01
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01Research focus

What I work on, and why.

My research brings computational biology and machine learning together to understand complex biological systems. I develop algorithms for biological data and build predictive models of biological phenomena, from where a viral spike protein is likely to mutate next to how a small molecule settles into an enzyme's active site.

My training spans computational methods and the biological sciences, and I try to work in the space between them. I'm currently a PhD candidate in chronophysics and chronobiology at the University of Sydney, where I study the rhythms and temporal dynamics of living systems.

  1. 01

    Machine Learning

    Deep learning for biological data and predictive modelling.

  2. 02

    Viral Evolution & Drug Discovery

    Mutation prediction, molecular docking and dynamics.

  3. 03

    Chronophysics & Chronobiology

    Mathematical models of biological rhythms and sleep.

  4. 04

    Bioinformatics

    Genomic data analysis and tools for biological research.

02Selected papers

All 18 publications →

    03Projects

    Research software I've built and shipped.

    [ Web platform · 2025 ]PRJ-01

    EVOLVEAI-based protein mutation prediction

    Predicts likely mutation sites and explores evolutionary phases of proteins, with interactive visualisations, real-time predictions and analysis tools. Published in J. Chem. Inf. Model.

    • Python
    • TypeScript
    • React
    • Stat. mech + ML
    [ Analysis suite · 2025 ]PRJ-02

    SIMANASimulation analysis

    Analysis for molecular dynamics trajectories: RMSD, RMSF, radius of gyration, SASA, hydrogen bonds, DCCM, PCA, Ramachandran plots, contact maps and B-factors in one place.

    • Python
    • React
    • Tailwind
    • MD
    [ LLM tool · 2022 ]PRJ-03

    ARIASArticle Research Intelligence & Summarization

    Summarises dense research articles and lets you ask questions about them in conversation, so you can get through the literature faster.

    • Deep learning
    • LangChain
    • Streamlit
    • OpenAI
    [ Pipeline ]PRJ-04

    Bioinformatics PipelineGenomic analysis, automated

    An automated pipeline for analysing and visualising genomic data, with machine learning built into the workflow.

    • Bioinformatics
    • Python

    04Path so far

    Education and research positions.

    Education
    1. 2024 — present

      PhD, Chronophysics & Chronobiology

      University of Sydney

    2. 2018 — 2020

      M.Tech, Biotechnology

      NIT Bhopal

    3. 2014 — 2018

      B.Tech, Biotechnology

      Dr. D.Y. Patil Biotechnology & Bioinformatics Institute

    Research experience
    1. 2021 — 2023

      Har Govind Khorana Junior Research Fellow

      IISER Kolkata

    2. Oct — Dec 2020

      Junior Research Fellow

      IISER Bhopal

    3. May 2019 — Jun 2020

      Master's dissertation student

      IISER Pune

    05Toolkit

    Skills, and where I've used them. Hover or tap a node; drag to rearrange.

    [ Skill graph ]FIG-05

    07Contact me

    Your message comes straight to my inbox.

    [ New message ]MSG-01