I am a PhD candidate in the Machine Learning Program at Georgia Tech (class of 2024). I was fortunate to have interned at Apple MLR, Cajal Neuroscience, and Meta for the past few years. Currently, I conduct my research in the Neural Data Science Lab advised by Prof. Eva L. Dyer. Previously, I got my BachelorÔÇÖs degree from Fudan University majoring in physics working on Quantum Hall effect and Superconductors.

I am looking for a full-time position starting in Fall 2024.

My research interests lie at the intersection of Machine (Deep) Learning, Computational/Cognitive Neuroscience, and Computer Vision. I am interested in developing more generalizable and interpretable deep learning methods for sequential systems and vision, and using them to accelerate scientific discovery. The research projects that I worked on, or am actively working on include:

  • Representation learning and generative models: Learning without explicit human annotation through self-supervision and generative modeling methods.
  • Interpretable deep learning methods: Building deep learning architectures 1) that are more interpretable under certain pre-defined conditions or assumptions, and 2) that align better to out-of-distribution domains and downstream tasks.
  • Multi-modal learning: Learning on multi-modal data in a more efficient and effective manner.

Outside from research, I do indoor climbing and I have two cats­čÉ▒.

Contact Me

  • My email address is rliu361{at}gatech{dot}edu.
  • My full CV is here. (Updated Oct, 2023)