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UCLA Samueli Announces 2024 Excellence in Teaching Awards

Awards dinner excellence in teaching awards

Apr 9, 2024

UCLA Samueli

Every year, the UCLA Samueli School of Engineering selects and recognizes outstanding achievements by a number of its alumni, faculty members and students who have excelled in various fields. Below are profiles of the recipients of the Eon Instrumentation Inc. Excellence in Teaching Award and the Northrop Grumman Excellence in Teaching Award.

2024 Awardees headshot3

Eon Instrumentation Inc. Excellence in Teaching Award
Todd Millstein
Chair and Professor of the Computer Science Department

Todd Millstein is the chair and a professor of the Computer Science Department at UCLA whose passion for teaching has inspired and helped many students. In 2016, Millstein designed the course “CS30: Principles and Practices of Computing” in an effort to address the disparity between students with high levels of exposure to coding in high school and those whose experiences were limited. The introductory course has improved students’ academic readiness for more advanced courses, and many cite the course as one of their most influential experiences in the major.

Millstein’s research focuses on programming languages and software verification, including network verification, security and reliability. He joined the UCLA faculty in 2003 and has taught courses on programming language theory and static type systems, as well as graduate research seminars on various related topics. An Amazon Scholar, Millstein has received many awards and recognitions including a National Science Foundation CAREER Award, a Northrop Grumman Excellence in Teaching Award from UCLA Samueli, a Microsoft Research Outstanding Collaborator Award, an IBM Faculty Award and a Facebook Research Award. He co-developed the open-source Batfish network configuration analysis software, which is used by major technology companies to ensure the security and reliability of their computer networks.


Jonathan Kao

Northrop Grumman Excellence in Teaching Award
Jonathan Kao
Associate Professor of Electrical and Computer Engineering

Jonathan Kao is an associate professor of electrical and computer engineering. Since joining the UCLA faculty in 2017, Kao has developed two new engineering courses — one on neural networks and deep learning, and the other on neural signal processing. They are among the most popular courses with the highest enrollment at UCLA Samueli. Kao’s classes have attracted students from more than 25 majors across campus and have received top marks in course reviews citing his passionate and engaging teaching style. Kao’s research interests lie at the intersection of basic neuroscience, neural engineering and modern artificial intelligence.

Kao has published studies at top venues on topics including brain-machine interfaces, deep learning, information theory, and the neuroscience of motor control, decision-making and anxiety. He is a member of the UCLA Neuroscience Interdepartmental Program and the UCLA Brain Research Institute. Among his many awards are a National Institutes of Health Director’s New Innovator Award, a National Science Foundation CAREER Award, and a Brain & Behavior Research Foundation National Alliance for Research on Schizophrenia and Depression Young Investigator Award. While studying for his bachelor’s, master’s and doctoral degrees in electrical engineering at Stanford University, Kao worked as a teaching assistant, graduate researcher and lecturer.

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