Xingjian Gao

Hi, I'm Xingjian Gao, a 5th-Year Master student from the Department of Electrical Engineering and Computer Sciences (EECS) at University of California, Berkeley. I major in Computer Science and Applied Mathematics during my undergraduate study at UC Berkeley. I'm from Changzhou, China.

Email / Resume / Courses

Research

I'm currently a student researcher in Berkeley Artificial Intelligence Research Lab (BAIR) advised by Prof. Yi Ma and in FHL Vive Center for Enhanced Reality's OpenARK Project advised by Dr. Allen Yang. I also work closely with Xili Dai from Prof. Heung-Yeung Shum's lab in HKUST(GZ). My research interest lies in interpretability of deep learning, sparse coding, generative models, and representation learning. I'm also interested in using deep learning to understand visual perception in primates and work with Prof. Doris Tsao on interpreting neural data with generative models.

Publications & Preprints

	Revisiting Sparse Convolutional Model for Visual Recognition Xili Dai, Mingyang Li, Pengyuan Zhai, Shengbang Tong, Xingjian Gao, Shaolun Huang, Zhihui Zhu, Chong You, Yi Ma NeurIPS 2022 (Accepted)
	Closed-Loop Transcription Via Convolutional Sparse Coding Xili Dai, Ke Chen, Shengbang Tong, Jingyuan Zhang, Xingjian Gao, Mingyang Li, Druv Pai, Yuexiang Zhai, Xiaojun Yuan, Heung-Yeung Shum, Lionel Ni, Yi Ma CPAL 2024 (Accepted)
	Exploring the Encoding Scheme of the Brain by Generating Images on Axes in a Common Space Xingjian Gao Berkeley EECS Masters Technical Report