Google Scholar for my full publication list.

Selected projects below. (* denotes equal contribution)

Large language models generate functional protein sequences across diverse families

Ali Madani, Ben Krause, Eric R. Greene, Subu Subramanian, Benjamin P. Mohr, James M. Holton, Jose Luis Olmos Jr., Caiming Xiong, Zachary Z. Sun, Richard Socher, James S. Fraser, Nikhil Naik

[Blog] [Paper] [News & Views] Nature Biotech

Deep Extrapolation for Attribute-Enhanced Generation

*Alvin Chan, *Ali Madani, Ben Krause, Nikhil Naik

[Blog] [Paper] [Code] NeurIPS 2021

BERTology Meets Biology: Interpreting Attention in Protein Language Models

Jesse Vig, Ali Madani, Lav R. Varshney, Caiming Xiong, Richard Socher, Nazneen Rajani

[Paper] [Code] [Yannic Kilcher] [The Batch] ICLR 2021

ProGen: Language Modeling for Protein Generation

Ali Madani, Bryan McCann, Nikhil Naik, Nitish Shirish Keskar, Namrata Anand, Raphael R. Eguchi, Po-Ssu Huang, Richard Socher

[Paper] [Blog] [VentureBeat] [Import AI] NeurIPS MLSB Workshop 2020

Deep Learning-enabled Breast Cancer Hormonal Receptor Status Determination from Base-level H&E Stains

Nikhil Naik, Ali Madani, Andre Esteva, Nitish Keskar, Michael Press, Dan Ruderman, David Agus, Richard Socher

[Paper] [VentureBeat] Nature Communications 2020

Fast and accurate view classification of echocardiograms using deep learning

Ali Madani, Ramy Arnaout, Mohammad R.K. Mofrad, Rima Arnaout

[Paper] [CNET] [IEEE Spectrum] Nature: Digital Medicine 2018