Columbia University Projects Receive Genesis Mission Funding

Three projects led by Columbia University professors have received Genesis Mission funding from the U.S. Department of Energy (DOE). The mission aims to integrate artificial intelligence into transformative scientific discovery, with the goal of doubling the productivity and impact of American science and engineering within a decade.

Kyle Bishop, professor of chemical engineering; Norman Christ, Ephraim Gildor Professor of Computational Theoretical Physics; and Kara Lamb, associate research scientist in the department of earth and environmental engineering, will receive awards.

“We are proud of the researchers whose projects have been selected for Genesis Mission awards through a highly competitive process,” said Jeannette Wing, Columbia’s executive vice president for research. 

The Genesis Mission unites DOE National Labs, industry, academia, and other partners to harness AI for breakthroughs in energy dominance, discovery science, and national security.

“The 278 projects selected today represent the very best of our nation’s scientific enterprise. The remarkable number of high-quality proposals we received demonstrates that America’s innovation pipeline is strong, and it points to even greater opportunities for future investment and continued expansion of the Genesis Mission portfolio,” said U.S. Secretary of Energy Chris Wright in a news release announcing the awards.

Columbia’s awardees have wide-ranging projects:

Bishop will develop an AI-enabled physical operating system for bio-programmable matter. Christ will use AI to speed up simulations of the nuclear force, the fundamental force that holds the quarks in an atomic nucleus together. Lamb will use AI and real-world observations to build much better computer models of clouds and precipitation, and to understand how confident those models are in their predictions.

“These projects reflect both the strength and breadth of Columbia research in lighting up scientific discovery through AI, and our collaborative spirit in working with national labs, industry, and other universities,” Wing said.

The Columbia University-led projects are:

AI-Enabled Physical Operating System for Bio-programmable Matter

Columbia lead: Kyle Bishop (Department of Chemical Engineering, Columbia Engineering), Professor of Chemical Engineering.

AI-accelerated sampling for critical slowing down in lattice QCD

Columbia lead: Norman H. Christ (Department of Physics, Faculty of Arts and Sciences), Ephraim Gildor Professor of Computational Theoretical Physics.

Cloud Microphysics Multi-Scale Modeling Moonshot (CM4): Creating the next generation of uncertainty-aware cloud models by leveraging multi-fidelity AI and DOE observations

Columbia lead: Kara Lamb (Department of Earth and Environmental Engineering, Columbia Engineering), Associate Research Scientist.

The projects led by other institutions, on which Columbia researchers are partnering are:

An Automated, Multimodal-AI-Enabled Cloud Chamber for Constraining Cloud Microphysical Processes in Earth System Models

Project lead: Brookhaven National Laboratory (BNL)

Columbia lead: Kara Lamb (Department of Earth and Environmental Engineering, Columbia Engineering), Associate Research Scientist.

Characterizing the Performance of HPC Workloads from Binary Executables

Project lead: Lawrence Livermore National Laboratory (LLNL)

Columbia lead: Tanvir Ahmed Khan (Department of Electrical Engineering, Columbia Engineering), Assistant Professor of Electrical Engineering. 

REACT: Reactor Exhaust And Core Twin -- Multi-fidelity AI Predictions for Safe, Integrated, and High-Performance Control

Project lead: Lehigh University

Columbia lead: Ben Zhu (Department of Applied Physics and Applied Mathematics, Columbia Engineering), Assistant Professor of Applied Physics.

Differentiable Physics-Integrated Generative Modeling for Complex Turbulent Flows in DOE Energy Systems

Project lead: Cornell University

Columbia lead: Ben Zhu (Department of Applied Physics and Applied Mathematics, Columbia Engineering), Assistant Professor of Applied Physics.

AI-Accelerated Supernova Burst Response with DUNE

Project lead: Duke University

Columbia lead: Georgia Karagiorgi (Department of Physics, Faculty of Arts and Sciences), Associate Professor of Physics.

Deployable Cavity Coupled Cold Atom Quantum Sensing Platform Driven by Agentic AI

Project lead: Brookhaven National Laboratory (BNL)

Columbia lead: Sebastian Will (Department of Physics, Faculty of Arts and Sciences), Associate Professor of Physics. 

Multimodal Enhancements to the Foundation Model for Nuclear and Particle Physics (FM4NPP)

Project lead: Lawrence Livermore National Laboratory (LLNL)

Columbia lead: William Allen Zajc (Department of Physics, Faculty of Arts and Sciences), I.I. Rabi Professor of Physics. 

Characterizing Jet Modification in the Quark-Gluon Plasma Using Unsupervised, Cycle-Consistent Generative Learning

Project lead: Research Foundation of the City University of New York (RFCUNY), on behalf of Baruch College

Columbia lead: William Allen Zajc (Department of Physics, Faculty of Arts and Sciences), I.I. Rabi Professor of Physics.

BIND: Biophysics-Informed Learning of Coordination for Metalloprotein Design

Project lead: Lawrence Livermore National Laboratory (LLNL)

Columbia lead: Mohammed AlQuraishi (Department of Systems Biology, Vagelos College of Physicians and Surgeons), Assistant Professor of Systems Biology.