Date and time: July 22, 2024 | 12:00 pm – 1:00 pm (CDT)
Speaker: Jordan Srour, PhD
Archive: Flier
About the talk
Making meaning of messy data is no easy feat, no matter the source of the data — a driving simulator or an archaeological site in Egypt. In this talk, Dr. Srour will describe a host of both supervised and unsupervised machine learning tools used in her research to uncover patterns in the interplay of psychological traits and overtaking behavior on two-lane roads, in the decision to stop or go at the onset of a yellow-light, and in the way by which ancient Egyptians managed their household space.
Speaker
Dr. Jordan Srour is an Associate Professor of Operations Management within the Adnan Kassar School of Business at the Lebanese American University. With a background in Logistics Management (PhD, Erasmus University), transportation engineering (MSE, UT Austin), and mathematics (BA, Carleton College), her research focuses on data analytics for management problems within the transportation, construction, and human resource sectors. Her research has been published in recognized journals, including Transportation Science, Transportation Research Part C and F, Journal of Construction Engineering and Management, Journal of Business Research, and Computers and Operations Research. Dr. Srour also serves as LAU’s Assistant Provost for Educational Resources and Innovation.