Research
My Google Scholar page is up to date on publications.
I enjoy studying data through the lens of structures and geometry, including low-dimensional embeddings learned from generative ML models. Right now, I am most interested in:
- Learning on graphs, networks
- Learning on manifolds
- Optimal transport, diffusion-based models
- Nonconvex optimization
- Federated learning, privacy-preserving machine learning
- Learning in low-label settings
- Self-supervised learning, representation learning
- Applications: science of science, medical and bioinformatics
I use tools in signal processing, machine learning, optimization, information theory, network science, and (high-dimensional) statistics.
Mentored students
Current
- Olawumi Olasunkanmi. UNC CS PhD. Co-advised by Stan Ahalt from SDSS and Chris Bizon from RENCI.
- Amartya Banerjee. UNC CS PhD. Co-advised by Caroline Moosmueller in Math.
- Saurav Raj Pandey. UNC CS PhD.
- Yidan Mei. UNC Math BS.
Previous
- Lu Cheng. UCLA Applied Math and Statistics BS. Advised honor’s thesis. Now Data Scientist at Meta.