Haibin Ling

Haibin Ling (凌海滨) (CV)
SUNY Empire Innovation Professor
Dept of Computer Science, Stony Brook University
Room 147, New Computer Science Bldg, Stony Brook, NY 11794-2424
hling AT cs.stonybrook.edu OR haibin.ling AT gmail.com | (+1) 631-632-8457

Short Bio: Haibin Ling received B.S. and M.S. from Peking University in 1997 and 2000, respectively, and Ph.D. from University of Maryland 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 UCLA; from 2007 to 2008, he worked for Siemens Corporate Research as a research scientist; and from 2008 to 2019, he was first an assistant and then an associate professor of Temple University. In fall 2019, he joined the Department of Computer Science of Stony Brook University, where he is now a SUNY Empire Innovation Professor. His research interests include computer vision, augmented reality, medical image analysis, visual privacy protection, and human computer interaction. He received Best Student Paper Award of ACM UIST (2003), Best Journal Paper Award at IEEE VR (2021), NSF CAREER Award (2014), Yahoo Faculty Research and Engagement Award (2019), and Amazon Machine Learning Research Award (2019). He serves or served as associate editors for IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), IEEE Trans. on Visualization and Computer Graphics (TVCG), Pattern Recognition (PR), and Computer Vision and Image Understanding (CVIU), and as Area Chairs for major computer vision relevant conferences such as CVPR, ICCV, ECCV, WACV, and ACM MM. He is a Fellow of IEEE.

Prospective students: please read HERE.
News

2024-03: A paper on edge detection (pdf) accepted by CVPR 2024.
2024-03: A paper on link modeling (pdf) accepted by PAMI.
2024-01: A paper on video projector compensation (pdf/code) accepted by IEEE VR 2024.
2023-11: BioDrone, an object tracking benchmark for drone captured videos, accepted to IJCV.
2023-08: A paper on projector-camera calibration (pdf/code) accepted by ISMAR 2023.
2023-07: Papers on active domain adaptation (pdf/code) and 6D pose estimation (pdf/code) accepted by ICCV 2023.
2023-07: A paper on transparent object tracking (pdf/code) accepted by IROS 2023.
2023-03: A paper on optical coherence Doppler tomograph (code) accepted by Communications Biology.