Guoqiang Yu | ECE | Virginia Tech


Guoqiang Yu

Picture of Guoqiang Yu

Virginia Tech Research Center - Arlington

Mailing Address:
Virginia Tech Research Center - Arlington
900 N. Glebe Road
Arlington, VA 22203


Associate Professor

Google Scholar Profile

Personal Website


Postdoctoral Fellow, Stanford University School of Medicine, 2012
Ph.D., Electrical Engineering, Virginia Tech, 2011
M.S., Electrical Engineering, Tsinghua University, China, 2004
B.S., Electronics Engineering, Shandong University, China, 2001

Teaching Interests:

Machine Learning, Pattern Recognition, Optimization, Stochastic Signal Processing.

Research Interests:

Data analytics, machine learning, signal and image processing, applied statistics, and their applications to developing computational bioinformatics and neuroinformatics tools, for the integrated modeling and analyses of various human diseases using multiplatform imaging, genomic, and molecular data.

Grants and Projects:
  • Multiple assistantships are available for Ph.D students with strong mathematical background and interest in modeling biomedical data as in the following federally funded projects.
  • Decoding astrocyte signaling in neural circuitry with novel computational modeling and analytical tools
  • Graphical time warping for complex time series: theory, algorithm and application
  • Brain activity analysis from large-scale bio-video data
  • Data analytics for live imaging
Selected Publications:
  • Title: Accurate quantification of astrocyte and neurotransmitter fluorescence dynamics for single-cell and population-level physiology
    Author(s): Yizhi Wang, Nicole V. DelRosso, Trisha V. Vaidyanathan, Michelle K. Cahill, Michael E. Reitman, Silvia Pittolo, Xuelong Mi, Guoqiang Yu*, Kira E. Poskanzer*
    Journal: Nature Neuroscience, October, 2019
  • Title: muSSP: Efficient Min-cost Flow Algorithm for Multi-object Tracking
    Author(s): CongchaoWang, YizhiWang, Yinxue Wang, Chiung-Ting Wu, Guoqiang Yu*
    Conference: Neural Information Processing Systems (NeurIPS), December 2019
  • Title: Developmental Heterogeneity of Microglia and Brain Myeloid Cells Revealed by Deep Single-Cell RNA Sequencing
    Author(s): Qingyun Li, Zuolin Cheng, Lu Zhou, Spyros Darmanis, Norma F Neff, Jennifer Okamoto, Gunsagar Gulati, Mariko L Bennett, Lu O Sun, Laura E Clarke, Julia Marschallinger, Guoqiang Yu*, Stephen R Quake*, Tony Wyss-Coray*, Ben A Barres*
    Journal: Neuron, December, 2018
  • Title: Automated Functional Analysis of Astrocytes from Chronic Time-Lapse Calcium Imaging Data
    Author(s): Yinxue Wang, Guilai Shi, David J Miller, Yizhi Wang, Congchao Wang, Gerald Broussard, Yue Wang, Lin Tian* and Guoqiang Yu*
    Journal: Frontiers in Neuroinformatics, July, 2017
  • Title: Graphical Time Warping for Joint Alignment of Multiple Curves
    Author(s): Yizhi Wang, David Miller, Kira Poskanzer, Yue Wang, Lin Tian, Guoqiang Yu*
    Conference: Neural Information Processing Systems (NIPS'16), December 2016
  • Title: AISAIC: a software suite for accurate identification of significant aberrations in cancers
    Author(s): Bai Zhang, Xuchu Hou, Xiguo Yuan, Ie-Ming Shih, Zhen Zhang, Robert Clarke, Roger R. Wang, Yi Fu, Subha Madhavan, Yue Wang, Guoqiang Yu*
    Journal: Bioinformatics, 2013
  • Title: BACOM: In silico detection of genomic deletion types and correction of normal cell contamination in copy number data
    Author(s): Guoqiang Yu, Bai Zhang, G. Steven Bova, Jianfeng Xu, Ie-Ming Shih, Yue Wang
    Journal: Bioinformatics, 2011
  • Title: PUGSVM: A caBIGTM analytical tool for multiclass gene selection and predictive classification
    Author(s): Guoqiang Yu, Huai Li, Sook Ha, Ie-Ming Shih, Robert Clarke, Eric P. Hoffman, Subha Madhavan, Jianhua Xuan, Yue Wang
    Journal: Bioinformatics, 2011
  • Title: Matched gene selection and committee classifier for molecular classification of heterogeneous diseases
    Author(s): Guoqiang Yu, Yuanjian Feng, David J. Miller, Jianhua Xuan, Eric P. Hoffman, Robert Clarke, Ben Davidson, Ie-Ming Shih, and Yue Wang
    Journal: Journal of Machine Learning Research, 2010
  • Title: Copy number analysis indicates monoclonal origin of lethal metastatic prostate cancer
    Author(s): Wennuan Liu, Sari Laitinen, Sofia Khan, Mauno Vihinen, Jeanne Kowalski, Guoqiang Yu, Li Chen, Srinivasan Yegnasubramanian, Jun Luo, Yue Wang, Jianfeng Xu, William B. Isaacs, Tapio Visakorpi, and G. Steven Bova
    Journal: Nature Medicine, 2009