Ye is part of Genesis Mission to protect AI from cyber threats

Feng Ye, an assistant professor in electrical and computer engineering at the University of Wisconsin-Madison, is a collaborator on a Genesis Mission project, a national effort aimed at leveraging AI to address some of the nation’s most pressing energy, scientific and engineering challenges.

Genesis Mission Phase I awards support teams as they design and test research workflows that integrate AI with scientific investigation. The projects, spanning fusion to critical minerals, are among 278 funded awards to national labs, companies, universities and non-profits in order to accelerate breakthroughs in energy, scientific discovery and national security through a new platform that combines AI, supercomputing, quantum systems and advanced scientific instruments.
 
Ye is part of the Department of Energy sponsored Gensis Mission project “Adversarial Robustness Framework for AI Models in Battery Management and Energy Science Workflows,” led by the University of North Dakota. 

The project ensures that AI models remain accurate, reliable, and secure in the presence of cyber threats, such as corrupted training data, deceptive sensor measurements, and software backdoors. These vulnerabilities can lead to inaccurate assessments of battery health and safety, potentially affecting the reliability of electric vehicles, grid-scale energy storage systems, and other critical energy infrastructure.

The research team will develop and evaluate a comprehensive framework for testing and improving the resilience of AI models used in battery management and related energy applications.

Ye leads research in federated learning, cybersecurity, and distributed AI systems. His work focuses on securing battery-management models that are trained collaboratively across multiple organizations without requiring sensitive operational data to be centralized or shared. 

By enabling secure, privacy-preserving collaboration and strengthening AI defenses against adversarial attacks, this research will help advance safer battery systems, more reliable distributed energy resources, and the trustworthy deployment of AI across critical energy and scientific workflows.