Yi Hong

Shanghai Jiao Tong University
Yi Hong 

Yi Hong
Tenure Track Associate Professor

Department of Computer Science and Engineering
Shanghai Jiao Tong University

Office: SEIEE 3-501
Email: yi.hong AT sjtu DOT edu DOT cn

I am a tenure track associate professor in the Department of Computer Science and Engineering at the Shanghai Jiao Tong University (SJTU) since 2021. My research interests lie in the area of image and shape analysis and AI in medical imaging. I am interested in developing computational methodologies for image understanding problems in the fields of medical image analysis and computer vision. I am also excited in interdisciplinary research, collaborating and working with researchers from related fields.

Before joining SJTU, I worked as a tenure track assistant professor in the Department of Computer Science at the University of Georgia. In 2016, I received my Ph.D. degree in Computer Science from the University of North Carolina at Chapel Hill, under the supervision of Dr. Marc Niethammer. I am a recipient of the 2014 MICCAI young scientist award (a.k.a., student best paper award) and a 2015 UNC dissertation completion fellowship.


  • June 2021:  Our paper on ASC-Net: Adversarial-based Selective Network for Unsupervised Anomaly Segmentation was accepted by MICCAI 2021.

  • Feb. 2021:  Our paper on MDA-Net: Multi-Dimensional Attention-Based Neural Network for 3D Image Segmentation was accepted by ISBI 2021 for oral presentation.

  • Jan. 2021:  I joined Shanghai Jiao Tong University.

  • Jan. 2020:  Our paper on Hybrid Cascaded Neural Network for Liver Lesion Segmentation was accepted by ISBI 2020.

  • Jan. 2020:  Our paper on SA-Net: Robust State-Action Recognition for Learning from Observations was accepted by ICRA 2020.

  • May 2018:  Our paper on CompNet: Complementary Segmentation Network for Brain MRI Extraction was accepted by MICCAI 2018 as a spotlight.

  • May 2018:  Our paper on Predictive Image Regression for Longitudinal Studies with Missing Data was accepted by MIDL 2018.

  • May 2018:  Our paper on Genetic Load Determines Atrophy in Hand Cortico-Striatal Pathways in Presymptomatic Huntington's Disease was accepted by Human Brain Mapping.

  • June 2017:  Our paper on Fast Geodesic Regression for Population-Based Image Analysis was accepted by MICCAI 2017 for oral presentation.

  • Jan. 2017:  Our paper on Regression Uncertainty on the Grassmannian was accepted by AISTATS 2017 for oral presentation.


I am looking for self-motivated undergraduate, master, and Ph.D. students to join my research group. Prior research experience in image analysis, deep learning, optimization, statistical shape analysis, or other related areas is a plus. If you are interested in my research and in working with me, please send me your CV or stop by my office if you are at SJTU.