About
Ke Xu is a Master's student in Data Science at Vanderbilt University, with research interests spanning machine learning design, deep learning, large language models, and database design. Previously, at the UR Medicine Motion Lab, he designed a scalable PostgreSQL schema to normalize high-dimensional motion and EMG data and built an LSTM model for real-time classification of IMU spine motion sequences. At the Tovar Lab, he is currently contributing to an audio-visual embedding project comparing neural responses in children and adults.
Research Interests
Current Research Projects
Audiovisual Object Embeddings over Development
This project investigates how visual and auditory semantic embeddings evolve over the course of development, driven by sensory experiences and learning. The research focuses specifically on how distinct visual and auditory representations independently develop and mature into adult-like semantic spaces. Using behavioral experiments, computational modeling, and neural validation through fMRI and MEG, we aim to characterize developmental trajectories and pinpoint how sensory experience shapes these semantic embeddings. Experiments will utilize real-world stimuli to explore the plasticity of semantic representations. Insights from this project will deepen our understanding of cognitive development