Four Princeton Engineering faculty members were recognized this year for excellence in teaching, service and mentoring.

The School of Engineering and Applied Science has honored professors Peter Ramadge and Jianqing Fan with awards for excellence in service and mentoring, respectively. These annual awards were created in 2023 by the engineering school to recognize faculty for some of their most important work beyond research and teaching.

The engineering school also recognized Michael Mueller with its annual Distinguished Teaching Award, and Arvind Narayanan was among four recipients of 2025 Graduate Mentoring Awards, co-sponsored by Princeton’s Graduate School and the McGraw Center for Teaching and Learning.

Peter Ramadge, Gordon Y.S. Wu Professor of Engineering and a professor of electrical and computer engineering, is the recipient of the SEAS Faculty Distinguished Service Award.

Ramadge, who is also the director of Princeton’s Center for Statistics and Machine Learning (CSML), is internationally recognized for his research in signal processing, machine learning and control theory, with applications ranging from neuroscience and robotics to video and image analysis.

In nominating Ramadge for the award, Jim Sturm, chair of electrical and computer engineering, wrote that “it’s hard to believe today, but in 2017 work on campus in machine learning/AI was just in its early stages, and Professor Ramadge’s leadership as CSML director was instrumental in developing this field at Princeton and bringing new faculty to campus.”

During Ramadge’s term as director of undergraduate studies, the electrical and computer engineering (ECE) department completely revamped its undergraduate curriculum, a structure that remains in place today. The new approach, unique within the engineering school at the time, emphasized both breadth and depth by requiring only four core courses and offering dozens of concentrations. Under his leadership, ECE also became one of the first engineering departments to require a senior thesis for all students.

Ramadge is renowned for his teaching and mentorship, having received multiple teaching awards, including the President’s Award for Distinguished Teaching and the Distinguished Teacher Award from the School of Engineering and Applied Science.

He has been praised by students for his extraordinary ability to break down technical material in a way that is easy to understand, and for his detailed lecture notes that have become an indispensable resource to many students who have taken his courses over the years.

He is an associated faculty member in the Program in Applied and Computational Mathematics, and is an active member of the neuroimaging analysis methods group at Princeton. He is the recipient of an IBM faculty development award and an Institute of Electrical and Electronics Engineers (IEEE) best paper award. He is a fellow of the IEEE and a member of the Society for Industrial and Applied Mathematics.

Ramadge joined Princeton in 1984 and was named Gordon Y.S. Wu Professor of Engineering in 2008. He earned a Ph.D. in electrical engineering from the University of Toronto, and undergraduate and master’s degrees from the University of Newcastle, Australia.

Jianqing Fan, the Frederick L. Moore, Class of 1918, Professor in Finance and a professor of operations research and financial engineering, is the recipient of the SEAS Excellence in Mentoring Award.

Fan’s research lies in the developments of statistical machine learning theory and methods and their applications in finance, economics, genomics and health. 

In nominating Fan for the award, Jason Klusowski, an assistant professor in the department, wrote that Fan “models intellectual excellence, generosity of spirit, and unwavering dedication to the success of others.”

Klusowski wrote that Fan’s mentorship “has profoundly shaped my development as a scholar, teacher and colleague,” and that Fan has also had significant impacts on the careers of graduate students and postdocs.

Yuling Yan, now a faculty member at the University of Wisconsin-Madison and a former Ph.D. student of Fan’s, emphasized Fan’s steady encouragement, thoughtful career guidance, and willingness to spend hours discussing ideas, writing, and professional development. He said that Fan’s open-door policy and patient, constructive feedback shaped his identity as a researcher and educator.

“It is all the more impressive that Jianqing is able to offer such consistent and impactful mentorship while maintaining a prolific and highly influential scholarly profile,” Klusowski wrote.

Fan’s research has earned him top honors including the Presidents’ Award from the Committee of Presidents of Statistical Societies (COPSS), the Morningside Gold Medal for Applied Mathematics, a Guggenheim Fellowship and, most recently, the 2025 Wald Memorial Award and Lectures from the Institute of Mathematical Statistics. In 2024 he received a commendation for outstanding teaching from Princeton’s School of Engineering and Applied Science. He is a fellow of several societies including the American Association for the Advancement of Science and the Institute of Mathematical Statistics.

Fan joined Princeton in 2003 following positions at the University of North Carolina-Chapel Hill, the University of California-Los Angeles, and the Chinese University of Hong Kong. He earned a Ph.D. from the University of California-Berkeley and a B.S. degree from Fudan University in China. He was named the Frederick L. Moore Professor of Finance in 2006; he chaired the Department of Operations Research and Financial Engineering from 2012 to 2015.

Michael Mueller is the recipient of Princeton Engineering’s annual Distinguished Teaching Award. Mueller, a professor of mechanical and aerospace engineering (MAE), was cited for his clear, organized lectures and passion for teaching and mentoring.

“His youthful enthusiasm for teaching lectures and his patient guidance during office hours honestly make it an absolute thrill to be learning from him,” said one student.

Former MAE department chair Howard Stone said that Mueller is “helping to prepare the next generation of scholars, and I value tremendously how he gives his time, energy and ideas toward this objective. Michael’s example of leadership in research and learning is tremendously valuable to our community.”

In addition to teaching courses including “Energy Conversion and the Environment” and “Simulation and Modeling of Fluid Flows,” Mueller has served as the department’s director of graduate studies and associate chair, and for the next academic year will serve as chair of the department.

Arvind Narayanan, professor of computer science, is a recipient of a 2025 Graduate Mentoring Award co-sponsored by the Graduate School and the McGraw Center for Teaching and Learning. He studies the societal impact of digital technologies, especially artificial intelligence. An expert on algorithmic fairness, artificial intelligence and privacy, he directs the Center for Information Technology Policy and has taught at Princeton since 2012.

A hallmark of his mentorship is his deep commitment to true partnership with graduate students, which often takes the form of co-authored papers in top-tier journals and shared presentations at high-profile conferences. “Arvind’s encouragement and insight in class and during office hours have formed the basis for several successful class projects turning into research publications and kickstarting research careers,” one doctoral student wrote.

Described as “transformative” in nearly every nomination, Narayanan balances guidance with independence, empowering early-stage researchers with a sense of ownership and insightful feedback that amplifies ideas.  

“Arvind is a true thought leader who inspires you to anticipate and tackle ambitious research problems,” one student said. “He repeatedly demonstrates his unique ability to anticipate shifts in research trends and encourages me to do work that bridges academic rigor and real-world impact.”

Another graduate student offered this powerful reflection: “Perhaps the strongest testimony to Arvind’s mentorship is that after working with him, I am strongly motivated to pursue a career in academia — despite working in a field where industry jobs are highly competitive and resulting in researchers leaving academia to join industry by the dozens.”

The announcement text on Narayanan’s award was adapted from an article by Colleen B. Donnelly.