UCLA Computer Scientist Receives NSF CAREER Award to Make Machine Learning Smarter and Safer
Cho-Jui Hsieh, an assistant professor of computer science at the UCLA Samueli School of Engineering, has received a National Science Foundation CAREER award, the agency’s highest honor for faculty members in the early stages of their teaching and research careers.
The award includes a five-year, $500,000 grant to support Hsieh’s research to improve how machine-learning models can incorporate the concept of safety as a critical component and make them more accessible to implement and use.
Machine learning is a type of artificial intelligence where computer algorithms learn and improve data analysis through repetition. While machine-learning AI has been in use and performed well within computer vision and natural language-processing systems, its adoption by real-world systems where safety is the overriding factor leaves much room for improvement. For example, a self-driving car using machine learning must always recognize and follow stop signs and traffic lights, even if the view is blocked or that visibility is low due to weather conditions. Hsieh will look to develop a more versatile, mathematically certified model that can meet specified safety criteria and account for additional complexity in variables.
Hsieh’s research focuses on developing new algorithms for large-scale, machine-learning problems. He received his Ph.D. from the University of Texas at Austin and joined UCLA in 2018, following three years as an assistant professor at UC Davis.
To date, more than 80 faculty members affiliated with UCLA Samueli have received an NSF CAREER Award.