I am currently a fourth-year PhD student studying Computer Science at Johns Hopkins University. It is my pleasure to be advised by Professor Junghoon Lee and Professor Russell Taylor. I received my master’s degree in computer science at Johns Hopkins University. I was fortunate to be advised by Professor Swaroop Vedula and Professor Gregory Hager. I received my bachelor’s degree in Computer Science and Technology from China University of Petroleum, Beijing, where I was supervised by Professor Liping Zhu.
\nMy current research interests are in medical image analysis and computer vision. More specifically, I’m interested in outcome prediction using medical images (such as CT and MRI) and radiation therapy plans, and personalized plan optimization. I’m also interested in generative models for medical images. I have experience in registration and basic image processing for mpMRIs.
\nKilleen, B. D.*, Wan, B.*, Kulkarni, A. V., Drenkow, N., Oberst, M., Yi, P. H., & Unberath, M. (2025). Towards Virtual Clinical Trials of Radiology AI with Conditional Generative Modeling. arXiv preprint arXiv:2502.09688. [post]
\nWan, B., McNutt, T., Quon, H., & Lee, J. (2025, April). Deep learning xerostomia prediction model with anatomy normalization and high-resolution class activation map. In Medical Imaging 2025: Image-Guided Procedures, Robotic Interventions, and Modeling (Vol. 13408, pp. 275-279). SPIE. [post]
\nGong, Z., Wan, B.*, Paranjape, J. N., Sikder, S., Patel, V. M., & Vedula, S. S. (2025). Evaluating the generalizability of video-based assessment of intraoperative surgical skill in capsulorhexis. International Journal of Computer Assisted Radiology and Surgery, 1-9.
\nWan, B., McNutt, T. R., Quon, H., & Lee, J. (2025, July). Explainable Xerostomia Prediction with Decoupled High Resolution Class Activation Map. In AAPM 67th Annual Meeting & Exhibition. AAPM.
\nWan, B., Peven, M., Hager, G., Sikder, S., & Vedula, S. S. (2024). Spatial-temporal attention for video-based assessment of intraoperative surgical skill. Scientific reports, 14(1), 26912. [post]
\nWan, B., McNutt, T., Ger, R., Quon, H., & Lee, J. (2024, April). Deep learning prediction of radiation-induced xerostomia with supervised contrastive pre-training and cluster-guided loss. In Medical Imaging 2024: Computer-Aided Diagnosis (Vol. 12927, pp. 286-291). SPIE. [post]
\nWan, B., Caffo, B., & Vedula, S. S. (2022). A unified framework on generalizability of clinical prediction models. Frontiers in Artificial Intelligence, 5, 872720.
\nZhu, L.*, Wan, B.*, Li, C., Tian, G., Hou, Y., & Yuan, K. Dyadic relational graph convolutional networks for skeleton-based human interaction recognition (Pattern Recognition, 2021). [post]
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