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.

I will join Apple AI/ML as a research scientist in 2024 Fall.

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)