👨🏼‍💻 I am a fifth-year Ph.D. candidate at Purdue University, where I am a member of the Machine Intelligence and Networked Data Science Group (MINDS) and the Laboratory for Translational Imaging of Microcirculation (TIM). I am co-advised by Prof. Abolfazl Hashemi and Prof. Behzad Sharif.

🔬 My research focuses on two areas: diffusion models and pretraining/fine-tuning of large-scale foundation models for cardiac MRI.

🌊 Diffusion Models: I develop efficient posterior sampling algorithms for solving inverse problems using diffusion model priors. My research combines Langevin Monte Carlo sampling, stochastic optimization, and generative modeling to design scalable and memory-efficient algorithms with provable convergence guarantees.

🫀 Cardiac MRI: I develop vision foundation models for cardiac MRI that leverage large-scale unlabeled data to improve downstream tasks such as segmentation, landmark detection, and disease classification, improving performance when only a small amount of expert-labeled data is available.

Research Interests

• Diffusion Models and Applications to Inverse Problems
• Vision Foundation Models for Cardiac MRI
• Multimodal Learning for 3D Medical Imaging
• Optimization and Langevin Monte Carlo Sampling Theory