Hey! I'm a MS/PhD student at MIT under Joseph Jacobson building AI methods for structural biology, molecular design, and molecular dynamics.
I'm interested in bridging the translation gap between computation and experimentation. I'm also a visiting researcher under Rhiju Das at Stanford building design tools for RNA.
I did my MS at Yale University advised by Rex Ying, and was at the National University of Singapore for college doing CS and Math, where I was advised
by Bryan Hooi.
I write about a ton of random seemingly-unconnected things (substack, old blog),
ML/AI4Bio (tech blog), and am also an active open-source contributor for ML tooling (github).
mail.rishabh.anand@gmail.com
github /
twitter /
linkedin /
scholar /
full CV
Publications
Stuff I find cool: symmetry-aware methods, biomolecule design, protein/molecular dynamics, literally anything structural-biology-related, mechanistic interpretability of LLMs.
(* equal contribution)
When Riemann flows with Wasserstein: Generative Modeling of Probability Distributions on Manifolds
Doron Haviv, Edward De Brouwer, Rishabh Anand, Rex Ying, Aïcha Bentaieb, Gabriele Scalia, Hector Corrada Bravo
NeurIPS 2026
Zatom-2: Multitask Pretraining on Atomistic Data for Generative Modeling across Domains
Miruna Cretu*, Alex Abrudan*, Antonia Panescu*, Tynan Perez*, Rishabh Anand*, N. Benjamin Erichson, Michael W. Mahoney, Samuel Blau, ..., Tuomas Knowles, Pietro Liò, Alex Morehead
Preprint. Under review.
Zatom-1: A Multimodal Flow Foundation Model for 3D Molecules and Materials
Alex Morehead*, Miruna Cretu*, Antonia Panescu*, Rishabh Anand*, Maurice Weiler*, Tynan Perez*, Samuel Blau, ..., Pietro Lio, ..., Rex Ying, ..., Michael W. Mahoney
Preprint. Under review.
Platonic Transformers: A Solid Choice for Equivariance
Mohammad Islam, Rishabh Anand*, David Wessels*, Friso de Kruiff, Thijs P. Kuipers, Rex Ying, Clara I. Sánchez, Sharvaree Vadgama, Georg Bökman, Erik J. Bekkers
ICML 2026
HELM: Hyperbolic Large Language Models via Mixture-of-Curvature Experts
Neil He*, Rishabh Anand*, Hiren Madhu, Ali Maatouk, Smita Krishnaswamy, Leandros Tassiulas, Menglin Yang, Rex Ying
NeurIPS 2025
RNA-FrameFlow: Flow Matching for de novo 3D RNA Backbone Design
Rishabh Anand*, Chaitanya K. Joshi*, Alex Morehead, Arian Jamasb, Charles Harris, Simon V. Mathis, Kieran Didi, Rex Ying, Bryan Hooi, Pietro Liò
TMLR 2025; MLCB 2024 (Oral); SPIGM Workshop, ICLR 2024 (Oral); AI4Science Workshop, ICLR 2024 (Spotlight); MoML 2024
gRNAde: Geometric Deep Learning for 3D RNA inverse design
Chaitanya K. Joshi, Arian R. Jamasb, Ramon Viñas, Charles Harris, Simon V. Mathis, Alex Morehead, Rishabh Anand, Pietro Liò
ICLR 2025 (Spotlight)
Recent Advancements in Deep Learning for Routing Problems
Chaitanya Joshi* and Rishabh Anand*
Blog Track, ICLR 2022 (Top 50% of submissions)
Pretrained Encoders are All You Need
Mina Khan, P Srivatsa, Advait Rane, Shriram Chenniappa, Rishabh Anand, Sherjil Ozair, Pattie Maes
Unsupervised RL Workshop, ICML 2021