Quanquan Gu, an assistant professor of computer science at the UCLA Samueli School of Engineering, has received an AWS Machine Learning Research Award from Amazon Web Services. AWS gives the award to academics on a quarterly basis to advance the frontiers of machine learning and its applications.
The award, which comes in the form of an unrestricted cash gift and AWS promotional credits, supports Gu’s research for developing a suite of principled and efficient deep reinforcement learning algorithms with provable performance guarantees. This research bridges the gap between the empirical success of those algorithms and traditional reinforcement learning theory and will establish the foundations of deep reinforcement learning, an essential process in making these algorithms more efficient and reliable in many critical application domains such as autonomous driving, artificial intelligence for personalized health care, and government decision making.
In March of this year, Gu and his team launched a model for predicting the spread of COVID-19. Now, that prediction model is one of 26 that feeds into a collective death forecast, and one of the seven models used for hospitalization forecast that informs predictions from the Centers for Disease Control and Prevention. Gu’s model is unique because it relies on epidemiology-driven machine learning rather than curve fitting techniques. The predictions that the model produces can measure the effectiveness of government policies and forecast possible surges in cases and hospitalizations.
Since 2017, the AWS Machine Learning Research Awards has assisted faculty, doctoral candidates and graduate students with research to advance the frontiers of machine learning and its application across a wide range of problems. These awards provide eligible researchers and university programs support as they develop open-source tools and research that benefit the machine learning community at large.