Jun 25
Coolidge Corner Theatre Brookline, MA
TicketsBrian Kulis
Associate Professor of Electrical & Computer Engineering, Boston University
Blade Runner— Replicants and A.I.
Program Description
Free outdoor 35mm screening in partnership with the Rose Kennedy Greenway! Before the film, Boston University Electrical and Computer Engineering Prof. Brian Kulis will discuss how A.I. informs the concept of replicants in Ridley Scott’s iconic sci-fi film.
This free screening will take place at sunset at the Greenway's Wharf District Park (located between Milk Street and Atlantic Avenue in Boston).
Film Synopsis
A blade runner must pursue and try to terminate four replicants who stole a ship in space and have returned to Earth to find their creator.
In the not-too-distant future, Los Angeles and the surrounding area has become a dystopian wasteland, heavily industrialized and overcrowded. Genetically engineered humanoid beings known as replicants are manufactured by the powerful Tyrell Corporation for use in dangerous off-world colonization. Retired police officer Rick Deckard (Harrison Ford), whose job was to track down replicants and assassinate them, is informed that four have come to Earth illegally. Called before his one-time superior (M. Emmett Walsh), Deckard is forced back into active duty to find and destroy the rogue replicants. Ridley Scott’s neo-noir classic initially polarized critics, but has since come to be regarded as one of the greatest sci-fi films of all time.
About the Speaker
Brian Kulis is an associate professor at Boston University, with appointments in the Faculty of Computing and Data Sciences, the Department of Electrical and Computer Engineering, the Department of Computer Science, and the Division of Systems Engineering. From 2019-2023, he was also an Amazon Scholar, working with the Alexa team.
Previously, he was the Peter J. Levine Career Development assistant professor at Boston University. Before joining Boston University, he was an assistant professor in Computer Science and in Statistics at Ohio State University, and prior to that was a postdoctoral fellow at UC Berkeley EECS. His research focuses on machine learning, statistics, computer vision, and large-scale optimization. He obtained his PhD in computer science from the University of Texas in 2008, and his BA degree from Cornell University in computer science and mathematics in 2003.
For his research, he has won three best paper awards at top-tier conferences: two at the International Conference on Machine Learning (in 2005 and 2007) and one at the IEEE Conference on Computer Vision and Pattern Recognition (in 2008). He was also the recipient of an NSF CAREER Award in 2015.