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A Cambridge PhD thesis in three research questions
Geometric Deep Learning for Molecular Modelling and Design: A personal scientific journey
Jan 8
•
Chaitanya K. Joshi
28
12
4
An AI researcher in the Cathedral of molecular biology
How we designed catalytic RNA functions, and what I learned holding a pipette at the MRC Laboratory of Molecular Biology.
Dec 18, 2025
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Chaitanya K. Joshi
24
3
4
An AlphaGo moment for RNA design
How our AI system, gRNAde, matched human experts at the complex game of RNA folding.
Dec 2, 2025
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Chaitanya K. Joshi
27
2
7
Beyond structure-based biomolecule design
Dynamics, black-box data, and the antedisciplinary frontier of biomolecule design
Nov 15, 2025
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Chaitanya K. Joshi
31
4
Towards transfer learning in molecular foundation models
Are multi-modal molecular foundation models learning transferable representations across biology and chemistry?
Jul 15, 2025
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Chaitanya K. Joshi
26
3
2
Equivariance is dead, long live equivariance?
When should you bake symmetries into your architecture versus just scaling up — an attempt at a nuanced take for molecular modelling.
Jun 1, 2025
•
Chaitanya K. Joshi
33
6
Molecular Modeling Club
Personal blog on generative AI for molecular design
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