Baharan Mirzasoleiman, an assistant professor of computer science at the UCLA Samueli School of Engineering, has received a National Science Foundation CAREER award. The prize includes a five-year, $529,000 grant to support Mirzasoleiman’s research to improve the efficiency and robustness of machine learning from massive data sets, with sustainability as a key goal.
Machine learning — a branch of artificial intelligence using computers to sift through massive and complex data sets to learn patterns and offer insights — has become a ubiquitous technique for a wide range of applications in health care, science, technology and business. But while machine learning algorithms have continuously been improved to enhance performance, the energy used and its resulting carbon footprint has also increased.
With the award, Mirzasoleiman will explore new ways to build powerful machine learning algorithms that, rather than training on the entire data set, will instead focus on relevant core subsets capable of offering the range of complexity needed for accurate, robust and efficient training, cutting down on the time and computing power required.