ACM Distinguished Speaker – Dr. Houbing Song: Real-Time Machine Learning for Quickest Detection

Join us as we host ACM Distinguished Speaker Dr. Houbing Song, the Director of NSF Center for Aviation Big Data Analytics and the Director of the Security and Optimization for Networked Globe Laboratory at UMBC.

Dr. Song will be lecturing on Quickest Detection, which refers to real-time detection of abrupt changes in the behavior of an observed signal or time series as quickly as possible after they occur, is essential to enable safety, security, and dependability of cyber-physical systems (CPS). Real-Time Machine Learning (RTML) has the potential to achieve quickest detection. However, Machine learning lacks the necessary mathematical framework to provide guarantees on correctness. The integration of machine learning with quickest detection not only creates new research opportunities with major societal implications, but also poses new research challenges in safety, security, and dependability. Dr.Song will present a comprehensive survey of the existing literature, identifying trends, challenges and presenting his own novel findings in the area.

This is a great opportunity for anyone interested in machine learning or cybersecurity who wishes to learn about some of the cutting-edge research in the field. This talk will take place in Iribe room 4105 on the 26th of February.

RSVP: https://forms.gle/UMBSFrfFVzB1Bpjq6