I am looking for a research internship (Summer 2025). Please let me know if you have opportunities in spatial-temporal modeling, multimodal learning, self-supervised learning, manifold learning, AI in healthcare, or related fields.

I am a Ph.D. student in computer science at Yale University (2022~) advised by Prof. Smita Krishnaswamy. I received my M.S. from Columbia University (2018~2020), and I did my undergraduate studies at Bucknell University, a liberal arts college featuring engineering education (2014~2018).

Research Areas  I primarily work on manifold learning, a subfield of deep learning that studies how to best organize the representations in the latent space of neural networks.

Most of my research involve direct applications to healthcare or medicine, via analysis of medical images and omics (genomics, transcriptomics, proteomics) data. I also work on fusing multiple modalities, modeling time-varying dynamics, and learning from limited or no labels.

In the remaining years of my Ph.D., I would like to spend more time on taming neural networks, including generative models, to better comply with constraints such as physical laws, with applications in modeling the natural progression of diseases in time-varying medical images.

Experience  Prior to my Ph.D., I first served as a full-time research assistant at Columbia University Medical Center (2020) in a medical imaging lab. The next year, I went to the industry and joined a startup company Matic (2021) and developed SLAM algorithms for housekeeping robots. Following that, I worked as a Senior Research Scientist at GE Healthcare (2021~2022), on deep learning in medical imaging applications, where I co-invented 2 patents.