Yichen (Henry) Liu

Hi and welcome to my personal website!

I’m a reasearch assistant at Maizie Zhou’s lab, Vanderbilt University. My research interests lie primarily in the area of computational genomics, computational neuroscience and deep learning etc. I did my bachelors at School of Information and Communication Engineering, University of Electronic Science and Technology of China

Education

University of Electronic Science and Technology of China

2016-2020 Sichuan, China

Vanderbilt University

Feb 2021 - Now TN, USA

Research Experience

  1. Research Assistant at MediaLab (Jan 2019-Jun 2020 Sichuan, China)
    • Participated in the design of a Deep Neural Networks based car brand recognition system
  2. Summer intern at Stanford (Jul-Sep 2019 CA, USA)
    • Participated in the design of Aquila_stLFR, a diploid genome assembly based structural variant calling package for stLFR linked-reads and published it to Bioconda.
  3. Research Assistant at Maizie Zhou’s Lab (Feb 2021 - Now TN, USA)
    • Simulated the short-term working memory by training Recurrent Neural Networks on series of cognitive tasks, and analyzed the neuron patterns in different maturation stages
    • Evaluated current state-of-art long read based structural variant callers against multiple long read sequencing datasets, and designed comprehensive comparisons to reveal their properties under different scenarios

Peer-reviewed Publications

  1. Liu, Y. H., Zhu, J., Constantinidis, C., & Zhou, X. (2021). Emergence of prefrontal neuron maturation properties by training recurrent neural networks in cognitive tasks. Iscience, 24(10), 103178.
    paper link
  2. Liu, Y. H., Grubbs, G. L., Zhang, L., Fang, X., Dill, D. L., Sidow, A., & Zhou, X. (2021). Aquila_stLFR: diploid genome assembly based structural variant calling package for stLFR linked-reads. Bioinformatics Advances, 1(1), vbab007.
    paper link
  3. Xie, Y., Liu, Y. H., Constantinidis, C., & Zhou, X. (2022). Neural Mechanisms of Working Memory Accuracy Revealed by Recurrent Neural Networks. Frontiers in Systems Neuroscience, 16.
    paper link
  4. Liu, Y. H., Luo C., Golding S. G., Ioffe J. B., & Zhou, X. (2022). Methods for structural variant detection with long-read sequencing data. Under review
  5. Luo C., Liu, Y. H., Datar P. A., & Zhou, X. (2022). Haplotype-phasing of long-read HiFi data to enhance structural variant detection through a Skip-Gram model. Under review

Teaching Experience

Teaching Assistant at Vanderbilt University

  1. CS 4278-02 Principle of Software Engineering (2021 Fall)
  2. BME 2900/3900W Biomedical Engineering Lab (2022 Spring)
  3. CS 3262-21-22 Applied Machine Learning (2022 Fall)

Mentoring Activities

Undergraduate Students

Master’s Students