Uploaded April 2026 | Updated September 2026, 2 weeks ago
Models, Inference, and Algorithms | April 1, 2026
Broad Institute of MIT and Harvard
Meeting: Multi-Scale Modeling of Cellular Responses to Perturbation with STATE
Abhinav Adduri
Machine Learning Research Scientist, Arc Institute
Seminar Abstract:
The ability to engineer cell states—driving cells from one functional identity to another—holds immense promise for regenerative medicine and disease modeling. However, the search space for genetic perturbations and experimental conditions is vast. In this seminar, Yusuf Roohani discusses how artificial intelligence and large-scale foundation models are being leveraged to predict and navigate these complex landscapes. He focuses on the development of deep learning frameworks that can prioritize candidate genes for reprogramming and predict the results of categorical perturbations, effectively enabling the systematic engineering of desired cellular phenotypes.
About MIA:
The Models, Inference & Algorithms (MIA) Initiative at the Broad Institute supports learning and collaboration across the interface of biology and medicine with mathematics, statistics, machine learning, and computer science. Our weekly meetings are open and pedagogical, emphasizing lucid exposition of computational ideas over rapid-fire communication of results.
MIA is hosted by the Eric and Wendy Schmidt Center at the Broad Institute.
Relevant Links:
MIA Website: broadinstitute.org/mia
MIA YouTube Playlist: broad.io/MIAPlaylist
Arc Institute: arcinstitute.org
Copyright Broad Institute, 2026. All rights reserved.
Models, Inference, and Algorithms | April 1, 2026
Broad Institute of MIT and Harvard
Meeting: Multi-Scale Modeling of Cellular Responses to Perturbation with STATE
Abhinav Adduri
Machine Learning Research Scientist, Arc Institute
Seminar Abstract:
The ability to engineer cell states—driving cells from one functional identity to another—holds immense promise for regenerative medicine and disease modeling. However, the search space for genetic perturbations and experimental conditions is vast. In this seminar, Yusuf Roohani discusses how artificial intelligence and large-scale foundation models are being leveraged to predict and navigate these complex landscapes. He focuses on the development of deep learning frameworks that can prioritize candidate genes for reprogramming and predict the results of categorical perturbations, effectively enabling the systematic engineering of desired cellular phenotypes.
About MIA:
The Models, Inference & Algorithms (MIA) Initiative at the Broad Institute supports learning and collaboration across the interface of biology and medicine with mathematics, statistics, machine learning, and computer science. Our weekly meetings are open and pedagogical, emphasizing lucid exposition of computational ideas over rapid-fire communication of results.
MIA is hosted by the Eric and Wendy Schmidt Center at the Broad Institute.
Relevant Links:
MIA Website: broadinstitute.org/mia
MIA YouTube Playlist: broad.io/MIAPlaylist
Arc Institute: arcinstitute.org
Copyright Broad Institute, 2026. All rights reserved.
