Education
- Beijing Institute of Technology 2017-2021
- B.Sc. in Automation
- Beijing Institute of Technology 2021-2024
- M.Sc. in Control Science and Engineering
- Max Planck Institute for Human Cognitive and Brain Sciences & Leipzig University (IMPRS CoNI) 2024-today
- Ph.D. in Physics
Research Interest
Xin is a doctoral researcher at MPI CBS, supervised by Nikolaus Weiskopf (Department of Neurophysics) and Nico Scherf. He works on adapting pretrained generative models to new tasks and conditions through fine-tuning and test-time adaptation, currently developing these ideas for diffusion models with simulation-based inference and inverse problems as testbeds. His PhD project is on deep learning reconstruction for fast, ultra-high-resolution MRI. Before his PhD, he worked on medical image analysis, including cardiac MRI segmentation and CT-based assessment of pulmonary hypertension.
Research keywords: diffusion models, test-time adaptation, fine-tuning, simulation-based inference, inverse problems, MRI reconstruction
Publications
- X. Zhao, N. Scherf, R. Trampel, K. J. Pine, N. Weiskopf. Spectra: Exact Component Transport for Test-Time Prior Adaptation in Simulation-Based Inference. arXiv:2610.08021, 2026. [arXiv] [Code]
- H. Xie*, X. Zhao*, N. Zhang, et al. Machine Learning–Based Hemodynamics Quantitative Assessment of Pulmonary Circulation Using Computed Tomographic Pulmonary Angiography. International Journal of Cardiology, 2025. (*equal contribution)
- X. Zhao, T. Wang, J. Chen, B. Jiang, H. Li, N. Zhang, G. Yang, S. Chai. GLRP: Global and Local Contrastive Learning Based on Relative Position for Medical Image Segmentation on Cardiac MRI. International Journal of Imaging Systems and Technology, 2024.
- N. Zhang*, X. Zhao*, et al. Machine Learning Based on Computed Tomography Pulmonary Angiography in Evaluating Pulmonary Artery Pressure in Patients with Pulmonary Hypertension. Journal of Clinical Medicine, 2023. (*equal contribution)
