Yi Hong
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Yi Hong Department of Computer Science and Engineering Office: SEIEE 3-533 |
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.
News
Aug. 2024: Our paper on Alifuse: Aligning and Fusing Multimodal Medical Data for Computer-Aided Diagnosis was accepted by BIBM 2024.
Aug. 2024: Our paper on Enhancing Atlas Construction via Edge-Assisted 3D Latent Diffusion Models for Brain MRI Generation was accepted by BIBM 2024.
July 2024: Our paper on SMART: Self-Weighted Multimodal Fusion for Diagnostics of Neurodegenerative Disorders was accepted by ACM Multimedia 2024.
May 2024: Our paper on NODER: Image Sequence Regression Based on Neural Ordinary Differential Equations was early accepted by MICCAI 2024.
Oct. 2023: Our paper on LongFormer: Longitudinal Transformer for Alzheimer’s Disease Classification with Structural MRIs was accepted by WACV 2024.
Oct. 2023: Our paper on Pretrain Once and Finetune Many Times: How Pretraining Benefits Brain MRI Segmentation was accepted by BIBM 2023.
July 2023: Our paper on R2Net: Efficient and Flexible Diffeomorphic Image Registration Using Lipschitz Continuous Residual Networks was accepted by Medial Image Analysis.
July 2023: Our paper on MetaRegNet: Metamorphic Image Registration Using Flow-Driven Residual Networks was accepted by MICCAI 2023 workshop CMMCA.
June 2023: Our paper on A2FSeg: Adaptive Multi-Modal Fusion Network for Medical Image Segmentation was early accepted by MICCAI 2023.
Openings
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.