4 faculty chosen for NSF CAREER recognition

WEST LAFAYETTE, Ind. — Four Purdue faculty members have been singled out for Faculty Early Career Development (CAREER) awards from the National Science Foundation.

NSF’s CAREER program provides the foundation’s most prestigious awards in support of early-career faculty who have the potential to serve as academic role models in research and education.

NSF announces CAREER awards throughout the year. Faculty listed below were notified of their awards between Jan. 1 and July 1 of this year. Receiving recognition and funding are:

Antonio Bianchi, associate professor of computer science in the College of Science, who will receive $580,000 for his project titled “Toward a Principled Methodology for Trusted Software Patching” through March 2030. Bianchi is developing new tools to help fix old or unsupported software — especially software for which the original source code is missing. Millions of devices run outdated programs that can’t be updated easily, making them easy targets for hackers. Bianchi’s research focuses on safely patching these systems directly at the binary or machine-code level without introducing new bugs or breaking the software. His team is building methods to test and explain patches that are trustworthy and practical in protecting vulnerable devices from security threats. The work is aimed at making software updates faster, safer and more reliable for everything from smart devices to critical infrastructure.

Yuan Gao, assistant professor of mathematics in the College of Science, who is being recognized with a CAREER award of $519,000 through May 2030 for her project called “Fluctuation Estimate, Selection Principle and Transition Paths for Multiscale Interacting Dynamics on Complex Structure.” Gao is developing new mathematical tools to help predict and better understand rare but powerful events — like sudden shifts in protein structures, evolutionary changes or even rapid changes in public opinion. These events happen in complex systems in which parts or people interact with one another and even small changes can have big effects. Her research will create ways to identify hidden patterns and better estimate when and how these rare events might occur. The work could lead to breakthroughs in fields like biology, drug development, materials science and social behavior, while also offering hands-on research opportunities for students.

Can Li, assistant professor of chemical engineering in the College of Engineering, who is receiving a grant of $500,000 for his project titled “Novel Neural Network Architectures Inspired by Optimization Algorithms.” Li’s team is developing a novel form of artificial intelligence model called optimization-inspired neural networks (OINNs) to make machine learning more reliable and understandable in chemical engineering. Traditional AI models, while powerful, often act like “black boxes” and can ignore important physical laws — an issue when safety is critical. OINNs aim to fix this by building those rules directly into the system, ensuring accurate and realistic results. The project also will include educational efforts ranging from updating a Purdue course to engaging K-12 students and teachers, helping train future engineers to use AI responsibly and effectively. Li’s CAREER Award provides funding through May 2030. 

Lauren Ann Metskas, assistant professor of biology and chemistry in the College of Science, who, through May 2030, will receive $938,000 in CAREER funding for her project called “Assembly and Supramolecular Organization of Bacterial Microcompartments.” The project endeavors to understand how certain bacteria naturally build tiny, protein-based “compartments” inside their cells that act like specialized mini factories. These compartments help bacteria carry out important chemical reactions more efficiently. The research focuses on figuring out how these structures come together and organize themselves like puzzle pieces fitting together. By learning how these bacterial compartments form and function, scientists hope to apply that knowledge to create new tools in medicine, energy and environmental science, such as better ways to deliver drugs or break down pollutants.

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