I work at the intersection of AI and cardiovascular biomechanics, developing next-generation tools for medical image segmentation, vascular geometry synthesis, and fast, accurate flow modeling. My research pushes the boundaries of image-based CFD by integrating deep learning, generative models, and differentiable solvers to make cardiovascular analysis more robust, scalable, and clinically impactful. I also explore uncertainty quantification and AI-driven design applications. If you’re interested in similar topics, feel free to reach out—I’m always excited to brainstorm ideas, exchange methods, and spark new collaborations!
Education
- Bachelor’s in Thermal Engineering, Tsinghua University
- Master’s in Mechanical Engineering and Materials Science, Washington University in St. Louis
- Ph.D. in Aerospace and Mechanical Engineering, University of Notre Dame (expected Winter 2025)
Upcoming events
- I will be attending USNCCM18 on July 20 at Chicago! See you guys there!
- I am entering the academic job market this year for faculty positions focused on scientific machine learning, computational fluid dynamics, and cardiovascular flow.
- I will be teaching AME 40411: Introduction to Artificial Intelligence this fall at the University of Notre Dame.