I am a 4th-year PhD student in the Machine Learning Program at Georgia Tech (class of 2024). I conduct my research in the Neural Data Science Lab advised by Prof. Eva L. Dyer. I got my BachelorÔÇÖs degree from Fudan University majoring in physics.

My research interests lie at the intersection of Machine (Deep) Learning, Computational Neuroscience, and Computer Vision. I am curious about how deep learning could be used to accelerate scientific discovery, and thus how to design better deep learning models for science. The research projects that I worked on, or am actively working on include:

  • Representation learning: Developing self-supervised learning and generative learning methods to obtain robust representation of neural data without relying on explicit human annotation.
  • Interpretable deep learning methods: Building deep learning architectures that are interpretable and identifiable under certain pre-defined conditions or assumptions.
  • Image segmentation: Efficient methods for image segmentation with limited or noisy annotations, explicit constraints, or topological/geometrical priors.

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 Sept, 2022)
  • My one-page resume is here. (Updated Oct, 2021)

I might have a neural-recording/time-series related project that I plan to work on starting early September 2023. I am happy to advise and collaborate with a MS/Undergrad student with strong deep learning background on this project. If you are a current Georgia Tech MS/Undergrad student and interested in this research area, feel free to send me an email.