Haibin Ling

Haibin Ling (凌海滨) (CV)
Chair Professor
Dept of Artificial Intelligence, Westlake University
Hangzhou, China
haibin.ling AT gmail.com

Short Bio: Haibin Ling received his B.S. and M.S. degrees from Peking University, and his Ph.D. from the University of Maryland. He worked as an assistant researcher at Microsoft Research Asia (2000–2001), a postdoctoral researcher at the UCLA (2006–2007), and a research scientist at Siemens Corporate Research (2007–2008). He then served as an Assistant Professor (2008–2014) and Associate Professor (2014–2019) at Temple University, and as a SUNY Empire Innovation Professor in the Department of Computer Science at Stony Brook University (2019-2025). In 2025, he joined Westlake University as a Chair Professor in the Department of Artificial Intelligence. His research interests span computer vision, augmented reality, medical image analysis, machine learning, and AI for science. His honors include the Best Student Paper Award at ACM UIST (2003), NSF CAREER Award (2014), Yahoo Faculty Research and Engagement Award (2019), Amazon Machine Learning Research Award (2019), and Best Journal Paper Award at IEEE VR (2021). He serves or served as Associate Editors for IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), IEEE Transactions on Visualization and Computer Graphics (TVCG), Computer Vision and Image Understanding (CVIU), and Pattern Recognition (PR). He has also served frequently as an Area Chair for major AI conferences including CVPR, ICCV, ECCV, ACM MM, and WACV. He is a Fellow of the IEEE.

Paper/Code/Data | gScholar | People | Tracking Benchmark |

Prospective students and lab members: we have multiple opennings for postdocs, PhD students, visiting students/interns, research assistants, etc.

If interested, please send your CV to me, with any materials that you view as relevant. Due to the high volume of requests, I might not respond to each individual email. I apologize for this, but please feel free to move on if I did not reply in two weeks. Thanks for understanding.
Currently the opennings are for all AI-related areas. In addition to traditional AI areas (e.g., computer vision, machine learning), I am looking for collaborators/students to work in AI for science (e.g., cryo-em image, quantum machine learning), for which biology and math/physical backgrounds are of particular importance.

News:

2025-07: RINDNet++, a fine-grained edge detector (pdf/code), accepted by IJCV.
2025-07: A paper on transformer ansatz for the density operator of steady states (pdf) accepted by Physical Review B.
2025-07: A paper on label placement accepted by IEEE VIS 2025/TVCG.
2025-06: A paper on sparse ODT reconstruction (pdf/code) and a paper on survival prediction (pdf/code) accepted by MICCAI 2025.
2025-06: VAPO, our new 6DoF pose estimation algorithm (pdf/code) accepted by IROS 2025.
2025-06: Ruyi Lian defended her dissertation, congratulations Dr. Lian!
2025-05: Shiva Vanaja Pandi and Pranav Chitale successfully defended their MS theses, congratulations!
2025-05: A paper on molucular graph explanation (pdf/code) accepted by ICML 2025.
2025-04: Jiaxiang Ren defended his dissertation, congratulations Dr. Ren!
2025-03: A paper on blood flow estimation (pdf/code) accepted by CVPR 2025.
2025-01: A paper on backdoor attack (pdf) and a paper on representation learning (pdf) accepted by ICLR 2025.