Yudi Xie (谢禹)

PhD student at MIT BCS. I build deep learning and probabilistic models to understand the brain and mind.

prof_pic.jpg

MIT building 46

43 Vassar St

Cambridge, MA 02139

My name is Yudi Xie, and I am currently pursuing my Ph.D. in Prof. James DiCarlo’s lab in the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology (MIT). Before embarking on this journey at MIT, I obtained my Bachelor’s degree in Physics from the University of Science and Technology of China (USTC).

My main research interest is at the intersection of computational neuroscience, cognitive science, and machine learning. Through the lens of machine learning, I utilize deep learning and probabilistic models to develop a computational framework for understanding the intricacies of the brain and mind. These computational models are then tested against empirical behavioral and neural data.

During my undergraduate years, I had the exceptional opportunity to do research in Prof. Naoshige Uchida’s lab at Harvard University. There, I used computational tools to investigate the influence of dopamine on novelty-seeking behaviors in mice. My interest in computational neuroscience research was initially sparked through my experience in Prof. Quan Wen’s lab at USTC, where I investigated the movement decisions of C. elegans.

latest posts

May 01, 2024 a post with tabs
Apr 29, 2024 a post with typograms
Apr 28, 2024 a post that can be cited

selected publications

  1. Learning only a handful of latent variables produces neural-aligned CNN models of the ventral stream
    Yudi Xie, Esther Alter, Jeremy Schwartz, and 1 more author
    2024
  2. bioRxiv
    Natural constraints explain working memory capacity limitations in sensory-cognitive models
    Yudi Xie, Yu Duan, Aohua Cheng, and 3 more authors
    bioRxiv, 2023
  3. CCN
    Human-like capacity limitation in multi-system models of working memory
    Yudi Xie, Yu Duan, Aohua Cheng, and 3 more authors
    2022
  4. Neuron
    Striatal dopamine explains novelty-induced behavioral dynamics and individual variability in threat prediction
    Korleki Akiti, Iku Tsutsui-Kimura, Yudi Xie, and 7 more authors
    Neuron, 2022
  5. Elife
    Flexible motor sequence generation during stereotyped escape responses
    Yuan Wang, Xiaoqian Zhang, Qi Xin, and 8 more authors
    Elife, 2020