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About me
I am a second-year PhD candidate in the Department of Radiological Sciences and the Department of Electrical and Computer Engineering at UCLA, where I am privileged to be co-advised by Prof. Kyung Sung and Prof. Robert Candler. Prior to joining UCLA, I received my Bachelor’s degree in Electronic Science and Engineering from Nanjing University in 2022, advised by Prof. Yang Li. During my undergraduate studies, I was also fortunate to work with Prof. Yuankai Huo at Vanderbilt University.
I am a member of the Sung Lab within MRRL Labs, collaborating with Prof. Kai Zhao and Dr. Qi Miao. I also engage in collaborative research with Prof. Wayne Brisbane’s group. My current research focuses on data-driven medical image enhancement, foundation models, and vision-language models. I was an Oncology - Deep Learning Researcher Intern at Bristol Myers Squibb during 2025 summer.
Outside of academia, I enjoy soccer, billiards, and bouldering. I am a fan of Arsenal and Miami Heat. I am also a long-time player of EA Sports FC.
🙌 Feel free to drop me an email if you are interested in my research projects or potential collaboration.
💻 I will be joining Samsung Research America (SRA) this summer as a Research Intern.
Modestly, Devoutly, Boldly.
- Medical Imaging
- Generative Models
- Foundation Models
- Vision-language Models
Ph.D. in Electrical and Computer Engineering, 2024-Now
University of California, Los Angeles
M.S. in Electrical and Computer Engineering, 2022-2024
University of California, Los Angeles
B.Eng. in Electronic Science and Engineering, 2018-2022
Nanjing University
Recent Posts
To record my thoughts and life (sometimes in Chinese)
Publications
Pang, Kaifeng, Qi Miao, Alex Ling Yu Hung, Changsuk Oh, Kai Zhao, Qiudi He, Marcel Dominik Nickel, Fei Han, and Kyunghyun Sung. “AICM: An Anatomical-Prior Integrated Conditional Consistency Model for Self-Supervised MRI Through-Plane Super-Resolution.” In 2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI), pp. 1-5. IEEE, 2026. (oral) [paper] [code]
Pang, Kaifeng, Qi Miao, Alex Ling Yu Hung, Kai Zhao, Eunsun Oh, Raymi Ramirez, Wayne Brisbane and Kyunghyun Sung. “MPR-Diff: a Self-Supervised Diffusion Model for Multi-Planar Reformation in Prostate Micro-Ultrasound Imaging.” In 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI), pp. 1-5. IEEE, 2025. [paper] [code] [poster]
Pang, Kaifeng, Kai Zhao, Alex Ling Yu Hung, Haoxin Zheng, Ran Yan, and Kyunghyun Sung. “NExpR: Neural Explicit Representation for fast arbitrary-scale medical image super-resolution.” Computers in Biology and Medicine 184 (2025): 109354. [paper] [code]
Pang, Kaifeng, Zuhayr Asad, Shilin Zhao, and Yuankai Huo. “MAg: a simple learning-based patient-level aggregation method for detecting microsatellite instability from whole-slide images.” In 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), pp. 1-4. IEEE, 2022. (oral) [paper] [code] [presentation]
Li, Junying, Qingyang Hou, Kaifeng Pang, Qi Miao, Alex Ling Yu Hung, Elif Aygun, Shu-Fu Shih, Qing Dai, Holden H. Wu, and Kyunghyun Sung. “CoDe: A Self-Supervised Consistency Model Framework for MRI Denoising.” In 2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI), pp. 1-5. IEEE, 2026. (oral) [paper] (co-first-author and corresponding author)
Zhao, Kai, Alex Ling Yu Hung, Kaifeng Pang, Parsa Hajipour, Holden Wu, Steve Raman, and Kyunghyun Sung. “PCa-Mamba: Spatiotemporal state space models for prostate cancer detection in multi-parametric MRI.” Medical image analysis (2026): 104033. [paper]
Zhao, Kai, Kaifeng Pang, Alex Ling Yu Hung, Haoxin Zheng, Ran Yan, and Kyunghyun Sung. “MRI Super-Resolution with Partial Diffusion Models.” IEEE Transactions on Medical Imaging (2024). [paper]
Zhao, Kai, Kaifeng Pang, Alex LingYu Hung, Haoxin Zheng, Ran Yan, and Kyunghyun Sung. “A Deep Learning-Based Framework for Highly Accelerated Prostate MR Dispersion Imaging.” Cancers 16, no. 17 (2024): 2983. [paper]
Hung, Alex Ling Yu, Haoxin Zheng, Kai Zhao, Kaifeng Pang, Demetri Terzopoulos, and Kyunghyun Sung. “Cross-Slice Attention and Evidential Critical Loss for Uncertainty-Aware Prostate Cancer Detection.” In International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 113-123. Cham: Springer Nature Switzerland, 2024. [paper]
Hung, Alex Ling Yu, Haoxin Zheng, Kai Zhao, Xiaoxi Du, Kaifeng Pang, Qi Miao, Steven S. Raman, Demetri Terzopoulos, and Kyunghyun Sung. “CSAM: A 2.5 D Cross-Slice Attention Module for Anisotropic Volumetric Medical Image Segmentation.” In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp. 5923-5932. 2024. [paper]
Please refer to my Google Scholar page for the full list.