AI Seminar: "Computer Vision and Applications in the Deep Learning Era" - Haibin Ling

Wednesday, February 17, 2021 - 10:00am to 11:00am
Zoom - contact for Zoom info.
Event Description: 


Viewing and understanding image data is the core goal of computer

vision. Although computer vision technologies have great practical

potential, but they have not been widely deployed in real-world

applications until the recent decade when deep learning-based

solutions began to sweep the entire field. In this talk, I will

present the research progresses on various computer vision tasks and

applications, based on my experiences cross the transition from

"traditional" solutions to deep learning ones. Specific topics to be

covered include visual recognition, object detection, visual matching,

visual tracking, 3D understanding, image and video enhancement,

spatial augmented reality, pose estimation, etc. Related publications,

data and source code can be found at


Bio: Haibin Ling received the B.S. and M.S. degrees from Peking

University in 1997 and 2000, respectively, and the Ph.D. degree from

the University of Maryland, College Park, in 2006. From 2000 to 2001,

he was an assistant researcher at Microsoft Research Asia. From 2006

to 2007, he worked as a postdoctoral scientist at the University of

California Los Angeles. In 2007, he joined Siemens Corporate Research

as a research scientist; then, from 2008 to 2019, he worked as a

faculty member of the Department of Computer Sciences at Temple

University. In fall 2019, he joined Stony Brook University as a SUNY

Empire Innovation Professor in the Department of Computer Science. His

research interests include computer vision, augmented reality, medical

image analysis, and human computer interaction. He received Best

Student Paper Award at ACM UIST (2003), NSF CAREER Award (2014), Yahoo

Faculty Research and Engagement Program Award (2019), and Amazon

Machine Learning Research Award (2019). He serves as Associate Editors

for several journals including IEEE Trans. on Pattern Analysis and

Machine Intelligence (PAMI), Pattern Recognition (PR), and Computer

Vision and Image Understanding (CVIU). He has served as Area Chairs

various times for CVPR and ECCV.


Hosted By: 
Steve Skiena
Computed Event Type: