2022 News

Professor Guido Montúfar received the 2022 Sloan Research Fellowship

Montúfar, who leads the Mathematical Machine Learning Group — centered at UCLA and the Max Planck Institute for Mathematics in the Sciences, in Germany — works on deep learning theory and mathematical machine learning. Through investigations of the geometry of data, hypothesis functions and parameters, he and his team are developing the mathematical foundations of deep learning and improving learning with neural networks. Montúfar is the recipient of a starting grant from the European Research Council and a CAREER award from the National Science Foundation, and he serves as research mentor with the Latinx Mathematicians Research Community. He and his team have organized a weekly online math machine learning seminar since 2020.

Please join me to congratulate Guido for receiving the prestigious Sloan Research Fellowship!

Read more details at this link from the UCLA Newsroom.

Professor Mark Handcock is co-author in a paper, published in the journal Nature Climate Change, which finds that Antarctic sea ice level could reach record low in 2022

The story on this research is posted in the UCLA Newsroom here.

UCLA researchers use Theory of Mind to improve Human Trust in Artificial Intelligence

Explainable Artificial Intelligence (XAI) models, through explanations, aim at making the underlying inference mechanism of AI systems transparent and interpretable to human users. Humans can easily be overwhelmed with too many or too detailed explanations; interactive communication process help in understanding the user and identify user-specific content for explanation, says Song-Chun Zhu, the project’s principal investigator and a professor of Statistics and Computer Science. So Zhu and his team set out to improve existing XAI models – to pose the explanation generation as an iterative process of communication between the human and the machine.

Arjun Reddy Akula, Ph.D. candidate at UCLA who led this work, said “In our framework, we let the machine and the user solve a collaborative task, but the machine’s mind and the human user’s mind only have a partial knowledge of the environment. Hence, the machine and user need to communicate with each other, using their partial knowledge, otherwise they would not be able to optimally solve the collaborative task”. He also said, “Our work will make it easier for non-expert AI human users to operate and understand the AI based systems”.

This work has been published in the prestigious Science journal and can be accessed here: https://www.cell.com/iscience/pdf/S2589-0042(21)01551-0.pdf