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
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 2007-2008, he worked for Siemens Corporate Research as a research scientist; and from 2008 to 2019, he was a faculty member of the Department of Computer Sciences for 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 in 2003 and NSF CAREER Award in 2014. He serves as associate editors for 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.
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Call for participation:  Int'l Workshop on Computer Vision for UAVs, in conjunction ECCV 2020.
News
  • 2020-06: A paper on 3D patient body modeling accepted by MICCAI 2020.
  • 2020-04: Peng Chu successfully defended his thesis, congratulations Dr. Chu!
  • 2020-02: A paper on graph matching and a paper on human object interaction accepted by CVPR 2020.
  • 2020-02: A paper on augmented reality accepted by IEEE VR, PDF.
  • 2020-01: A paper on visual SLAM accepted by ICRA, PDF.
  • 2020-01: A paper on video object segmentation accepted by PAMI, PDF.
  • 2019-12: Yu Pang successfully defended his thesis, congratulations Dr. Pang!
  • 2019-11: A paper on visual tracking accepted by PAMI, link.
  • 2019-11: CBNet object detection (AAAI 2020) code released, PDF | code.

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