Contact Information
Email: hojin.jang@vanderbilt.edu
Research Interests
I majored in Computer Science when I was in undergraduate course and received a Master degree in Brain and Cognitive engineering. During my master's research, I had experienced deep learning and applied it to functional MRI. Now I am working with Dr. Frank Tong at Vanderbilt University. I felt fascinated by various machine learning and deep learning techniques including convolutional neural network, recurrent neural network, reinforcement learning, and optimization theory. Also, I am very interested in visual mechanisms in the brain such as object recognition, visual memory and attention, and brain decoding. My research goal is to combine both fields to have a comprehensive understanding of the visual system.
Publications
Jang, H., & Tong, F. (2021). Convolutional neural networks trained with a developmental sequence of blurry to clear images reveal core differences between face and object processing. Journal of Vision, 21(12):6, 1-18.
Jang, H., McCormack, D., & Tong, F. (2021). Noise-trained deep neural networks effectively predict human vision and its neural responses to challenging images. PLoS Biology, 19(12):e3001418, 1-27.
Jang, H., Plis, S. M., Calhoun, V. D., & Lee, J. H. (2017). Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks. Neuroimage, 145, 314-328.