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.
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.
Deep learning for biological data and predictive modelling.
Mutation prediction, molecular docking and dynamics.
Mathematical models of biological rhythms and sleep.
Genomic data analysis and tools for biological research.
Research software I've built and shipped.
Catches the mechanical mistakes before a paper goes to a journal: uncited or uncaptioned figures and tables, reference list mismatches, broken cross-references, leftover tracked changes and placeholders. Runs locally and uses rules, not AI, so the text never leaves your machine.
Maps the labs you're considering for a PhD or postdoc and scores each on three separate axes: what you share, what scarce skill you bring, and what you'd learn there. The shortlist is built as a portfolio rather than the top-N most similar labs. Runs locally against Ollama, so your CV never leaves your laptop.
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.
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.
Summarises dense research articles and lets you ask questions about them in conversation, so you can get through the literature faster.
An automated pipeline for analysing and visualising genomic data, with machine learning built into the workflow.
Education and research positions.
University of Sydney
NIT Bhopal
Dr. D.Y. Patil Biotechnology & Bioinformatics Institute
IISER Kolkata
IISER Bhopal
IISER Pune
Skills, and where I've used them. Hover or tap a node; drag to rearrange.
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