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Yu, Guoqiang

Date：2019-09-30

     PI, IDG/McGovern Institute for Brain Research, Tsinghua University

     Professor,Department of Automation, Tsinghua University

    

     E-mail：yug@tsinghua.edu.cn

 

 
                             

 

[Research Focus]

Glia, Machine Learning, and Computational Brain Science. My main research area is the interdisciplinary field between computational science and brain science, that is, theoretical brain science or computational brain science. Our lab is interested in the mathematical models, theory and methods in analyzing and understanding the large-scale, complex and high-dimensional data of brain science. We are particularly interested in understanding the role of glia in the brain.

 

[Education & Experience]                           

2024.04 -                     IDG/McGovern Institute for Brain Research, Tsinghua University, PI
2023.08 -                     Department of Automation, Tsinghua University,　Professor
2022.08 - 2023.08       Virginia Tech, USA,     Professor
2018.08 - 2022.08       Virginia Tech, USA,     Associate Professor
2012.08 - 2018.08       Virginia Tech, USA,     Assistant Professor
2011.09 - 2012.08       Stanford University, USA,   Postdoctoral Fellow
2006.08 - 2011.09       Virginia Tech, USA,    Ph.D.
2001.09 - 2004.07       Tsinghua University, China,  Master of Science
1997.09 - 2001.07       Shandong University, China,  Bachelor of Science
 

 

[Selected Publications]                            

  • Xuelong Mi, Mengfan Wang, Alex Bo-Yuan Chen, Jing-Xuan Lim, Yizhi Wang, Misha Ahrens, Guoqiang Yu*, “BILCO: An Efficient Algorithm for Joint Alignment of Time Series”, Advances in Neural Information Processing Systems (NeurIPS’22), November 28, 2022. (*corresponding author)
  • Mengfan Wang, Boyu Lyu, Guoqiang Yu*, “ConvexVST: A Convex Optimization Approach to Variance-stabilizing Transformation”, The International Conference on Machine Learning (ICML’21), July 18, 2021. (*corresponding author).
  • Congchao Wang, Yizhi Wang, Guoqiang Yu*, “Efficient Global Multi-object Tracking Under Minimum-cost Circulation Framework”, IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), April, 2020. (*corresponding author).
  • Yizhi Wang, Congchao Wang, Petter Ranefall, Gerard Joey Broussard, Yinxue Wang, Guilai Shi, Boyu Lyu, Yue Wang, Lin Tian, Guoqiang Yu*, “SynQuant: An Automatic Tool to Quantify Synapses from Microscopy Images”, Bioinformatics, March 1, 2020. (*corresponding author).
  • Congchao Wang, Yizhi Wang, Yinxue Wang, Chiung-Ting Wu, Guoqiang Yu*, “muSSP: Efficient Min-cost Flow Algorithm for Multi-object Tracking”, Advances in Neural Information Processing Systems (NeurIPS’19), December 9, 2019. (*corresponding author). 
  • Yizhi Wang, Nicole V. DelRosso, Trisha V. Vaidyanathan, Michelle K. Cahill, Michael E. Reitman, Silvia Pittolo, Xuelong Mi, Guoqiang Yu*, Kira E. Poskanzer*, “Accurate quantification of astrocyte and neurotransmitter fluorescence dynamics for single-cell and population-level physiology”, Nature Neuroscience, September 30, 2019. (*corresponding author).   
  • Yizhi Wang, David J. Miller, Kira Poskanzer, Yue Wang, Lin Tian, Guoqiang Yu*, “Graphical Time Warping for Joint Alignment of Multiple Curves”, Advances in Neural Information Processing Systems (NIPS’16), 3648-3656, December, 2016 (*corresponding author).