Yifan Wu

I'm a 5-th year PhD student at the University of Pennsylvania, advised by James C. Gee. My research focuses on artificial intelligence, machine learning and computer vision, especially their applications in medical imaging and healthcare. Currently, I'm working on vision-language model, large language model, deformable image registration, and multi-view correspondence.

I am looking for full-time jobs starting Summer 2024.

Email: yfwu@seas.upenn.edu / Google Scholar

Selected Publications

	The Role of Chain-of-Thought in Complex Vision-Language Reasoning Task Yifan Wu, Pengchuan Zhang, Wenhan Xiong, Barlas Oguz, James C Gee, Yixin Nie Arxiv, 2023 Paper We found that GPT-4V can benefit significantly from the Chain-of-Thought prompt. We present the "Description then Decision" strategy, which improves Winoground task performance by 50%.
	Towards Establishing Dense Correspondence on Multiview Coronary Angiography: From Point-to-Point to Curve-to-Curve Query Matching Yifan Wu, Rohit Jena, Mehmet Gulsun, Vivek Singh, Puneet Sharma, James C Gee Arxiv, 2023 Paper We established dense correspondence in multi-view angiography by formulating it as a query matching problem and extending point matching to curve matching for enhanced topological awareness.
	NODEO: A Neural Ordinary Differential Equation Based Optimization Framework for Deformable Image Registration Yifan Wu, Tom Z Jiahao, Jiancong Wang, Paul A Yushkevich, M Ani Hsieh, James C Gee CVPR, 2022 Project Page/ Paper/ Supplementary We model each voxel as a moving particle and consider the set of all voxels in a 3D image as a high-dimensional dynamical system whose trajectory determines the targeted deformation field.
	Interpretable Identification of Interstitial Lung Disease (ILD) Associated Findings from CT Yifan Wu, Jiancong Wang, William D. Lindsay, Tarmily Wen, Jianbo Shi, and James C. Gee MICCAI, 2020 Paper Formulated the radiologic ILD findings identification as a multi-class classification problem given the raw thoracic CT dataset.
	From Image to Video Face Inpainting: Spatial-Temporal Nested GAN (STN-GAN) for Usability Recovery Yifan Wu, Vivek Singh, Ankur Kapoor WACV, 2020 Paper/ Video Result We propose to use constrained inpainting methods to recover usability of corrupted images, which are masked for privacy protection but complete images are required for further algorithm development.
	Towards Generating Personalized Volumetric Phantom from Patient's Surface Geometry Yifan Wu, Vivek Singh, Brian Teixeira, Kai Ma, Birgi Tamersoy, Andreas Krauss, and Terrence Chen MICCAI, 2019 Paper This paper presents a method to generate a volumetric phantom with internal anatomical structures from the patient?s skin surface geometry.
	Privacy-Protective-GAN for Face De-identification Yifan Wu, Fan Yang, and Haibin Ling Arxiv, 2018 Paper Defined the face-identification task by establishing an effective de-identification measurement: achieve privacy protection simultaneously preserving data utility. Proposed an end-to-end trainable framework to synthesize de-identified facial images.