I am a PhD candidate in the Machine Learning Program at Georgia Tech (class of 2024). I was fortunate to have interned at Apple AI/ML, 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 Bachelor’s degree from Fudan University majoring in physics working on Quantum Hall effect and Superconductors.

My research interests lie at the intersection of Machine (Deep) Learning, Computer Vision, and Computational/Cognitive Neuroscience. I am interested in developing large-scale learning methods that are more generalizable and explainable. The research projects that I worked on include:

• Large-scale Pretraining and Alignment for Time Series and Beyond: Develop large-scale transformers for effective training on massive amounts of data, and efficiently adapt/align them to specific downstream tasks based on needs.
• Representation Learning, Contrastive Methods, and Data Augmentation: Build and evaluate deep learning architectures to make sure they have a customizable and explainable representation space.
• Generative Modeling and Segmentation of Medical Images: Multiscale modeling, classification, and segmentation of brain structures.

Outside of research, I am a fan of indoor climbing, fine dining, and playing with my two lovely cats🐱.

Contact Me

• My email address is rliu361{at}gatech{dot}edu.
• My full CV is here. (Updated Feb, 2024)