Hi, I am Chen Liu, a PhD student in Computer Science at Yale University.
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.
I am generally over-booked on projects, but feel free to reach out for collaboration.
✔️ A simple and effective tool to generate your Google Scholar Citation World Map [Git]
🎉 [ICASSP 2025] ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images [Git] [PDF] [Slides]
🎉 [ICASSP 2025] DiffKillR: Killing and Recreating Diffeomorphisms for Cell Annotation in Dense Microscopy Images [Git] [PDF] [Slides]
🎉 [MICCAI 2024] CUTS: A deep learning and topological framework for multigranular unsupervised medical image segmentation [Git] [PDF] [Poster] [MICCAI2024]
🎉 [ICMLW 2023] A novel method to compute entropy and mutual information in neural net representations [Git] [PDF] [Blog] [Slides]
✔️ An on-the-fly evaluator for GANs, with a simple working example of DCGAN on SVHN [Git]
✔️ A guide to simulate bigger batch sizes beyond GPU capability [Git]