Do Hun (Don) Kim

Computer Science & Mathematics Undergraduate

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About

As a Computer Science and Mathematics major at Vanderbilt University, I am passionate about leveraging machine learning and software engineering to develop intelligent, real-world solutions. With a strong foundation in various programming languages and frameworks, I aspire to contribute to both AI research in computational neuroscience and impactful software engineering innovations. My goal is to develop brain-computer interfaces, neuroadaptive systems, and robust software solutions that enhance human-computer interaction and medical technology.

Research Interests

Neural Network Architectures Machine Learning Development

Current Research Projects

Audiovisual Object Embeddings over Development
Featured Project

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

Multimodal Learning Plasticity over Development

This project investigates the development of multimodal learning plasticity across different developmental stages. By employing novel stimuli with arbitrary audiovisual pairings, we will conduct both passive and active learning sessions including within immersive environments to assess how effectively these associations are retained over time. Through behavioral experiments and electroencephalography (EEG), we aim to characterize the developmental trajectory of multimodal learning and identify critical periods for such plasticity. The findings will provide insights into how sensory experiences shape cognitive development and inform applications in education and neurodevelopmental research.​