As of January 2024, TILOS Foundations team member Misha Belkin is the editor-in-chief of the Society for Industrial and Applied Mathematics (SIAM) Journal on Mathematics of Data Science (SIMODS), a leading journal on the foundations of data science.
Yahoo Finance || With prestigious National Science Foundation grant, Veteran-founded National University announces new bachelor’s degree helping active-duty military and Veterans up- and reskill for careers in data science and AI.
New Scientist || Generative AI tools such as chatbots may be able to help chip designers generate code and find software bugs.
UC San Diego Today || From the operating room to our homes and streets, robots are becoming increasingly integral to our daily activities. On November 14, 2023 the UC San Diego Contextual Robotics Institute hosted its eighth annual forum, bringing together robotics experts from industry and academia to discuss cutting-edge developments in the field that […]
Yale Daily News || Eleven months after ChatGPT’s release, Yale computer science professors discussed the carbon footprint associated with artificial intelligence and how growing industry management might better control its energy use.
UC San Diego Today || Experts from diverse disciplines explored the vast implications of artificial intelligence in a panel discussion moderated by Greg Horowitt, director of innovation design at UC San Diego. Panelists included David Danks, a professor of data science and philosophy at UC San Diego; Yusu Wang, a professor in the Halıcıoğlu Data […]
TILOS director Yusu Wang and Networks team co-lead Tara Javidi of UC San Diego represent TILOS at the National Science Foundation’s Artificial Intelligence Hill Day at the United States Capitol.
UC San Diego Today || TILOS Robotics team co-lead Henrik Christensen of UC San Diego on using AI for self-driving cars.
National University News || TILOS faculty help San Diego-based National University establish seven new career-relevant programs.
Forbes || TILOS Foundations team member Stefanie Jegelka of MIT on graph models for machine learning.
