About Me

About Me

Hi I'm Yiwen Liu. I am a Assistant Professor of Practice in the Department of Epidemiology and Biostatistics at the University of Arizona. My primary research interest focuses on theoretical and methodological developments in big data analytics, including statistical learning for high dimensional data, low-rank approximation and sparse representation of matrices, and multiple sources data integration.

Contact Info:
Email: yiwenliu@arizona.edu
Office: Drachman Hall 200

Education:
Ph.D., Department of Statistics, University of Georgia, 2013-2018
M.S., Department of Statistics, Central University of Finance and Economics, China, 2010-2013
B.S., Department of Statistics, Central University of Finance and Economics, China, 2006-2010

Research Interest:
Big data analytics, statistical learning in high dimensional data, multiple sources data integration, metabolomics, and bioinformatics.

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Publications

Publications

  1. Zhong, W., Liu, Y. and Zeng, P., 2021. A model-free variable screening method based on leverage score. Journal of the American Statistical Association (Theory and Methods), accepted.
  2. M. Zhang, Liu, Y., H. Zhou, J. Zhou, and J. Watkins., 2021. A novel non-linear dimension reduction approach to infer population structure for low-coverage sequencing data. BMC Bioinformatics, accepted.
  3. Sun, X., Liu, Y. and An, L., 2020. Ensemble dimensionality reduction and feature gene extraction for single-cell RNA-seq data. Nature Communications, 11(1), 1-9.
  4. Liu, Y., Xing, X. and Zhong, W., 2018. Sufficient Dimension Reduction for Tensor Data, in Handbook of Big Data Analytics. Springer.
  5. Liu, Y., Ma, P., Cassidy, P.A., Carmer, R., Zhang, G., Venkatraman, P., Brown, S.A., Pang, C.P., Zhong, W., Zhang, M. and Leung, Y.F., 2017. Statistical Analysis of Zebrafish Locomotor Behaviour by Generalized Linear Mixed Models. Scientific Reports, 7.
  6. Zhang, L., Xiang, L., Liu, Y., Venkatraman, P., Chong, L., Cho, J., Bonilla, S., Jin, Z.B., Pang, C.P., Ko, K.M. and Ma, P., 2016. A Naturally-Derived Compound Schisandrin B Enhanced Light Sensation in the pde6c Zebrafish Model of Retinal Degeneration. PLOS ONE, 11(3), p.e0149663.
  7. Liu, Y., Carmer, R., Zhang, G., Venkatraman, P., Brown, S.A., Pang, C.P., Zhang, M., Ma, P. and Leung, Y.F., 2015. Statistical Analysis of Zebrafish Locomotor Response. PLOS ONE, 10(10), p.e0139521.
Teaching

Teaching

Fall 2019

DATA 467: Introduction to Applied Regression and Generalized Linear Models

General Information:
Location and Time:
Chavez 303, MWF 8:00 am - 8:50 am
Office Hour:
Monday 9:00 - 11:00 am, Wednesday 9:00 - 10:00 am
Textbook:
1. Statistical Data Analytics: Foundations for Data Mining, Informatics,
and Knowledge Discovery by Walter W. Piegorsch.
2. Linear Models with R, 2nd Edition by Julian J. Faraway.

EPID/BIOS 450: Health Data Acquisition, Assessment, and Integration

General Information:
Location and Time:
HSIB, T,Th 9:30 - 10:45 am
Office Hour:
T,Th 10:45 - 11:40 am
Textbook:
1. R for Data Science, by Garrett Grolemund and Hadley Wickham.
2. Big Data and Health Analytics, by Katherine Marconi, Harold Lehmann,
Taylor and Francis Group, 2015.

Spring 2019

Math 464 Theory of Probability

General Information:
Location and Time:
PSYCH 305, Tuesday and Thursday 2:00 pm - 3:15 pm
Office Hour:
Monday and Tuesday 1:00 - 2:00 pm
Textbook:
Probability - An Introduction by Geoffrey Grimmett and Dominic Welsh (2nd edition).
Course Webpage:
 Visit course webpage: Probability An Introduction

Fall 2018

Math 122B First Semester Calculus

General Information:
Location and Time:
Cesar E Chavez 303, Monday to Friday 2:00 pm - 2:50 pm
Office Hour:
Monday 3:00 - 4:00 pm (ThinkTank), Tuesday 1:00 - 2:00 pm
Textbook:
Calculus Single Variable; Sixth Edition by Hughes-Hallett et al.
Course Webpage:
http://math.arizona.edu/~calc

Math 122A Functions for Calculus

General Information:
Time:
Monday to Thursday
Office Hour:
Monday 3:00 - 4:00 pm (ThinkTank), Tuesday 2:00 - 3:00 pm
Textbook:
Chapter 1 of Calculus Single Variable; Sixth Edition by Hughes-Hallett et al.
Course Webpage:
http://math.arizona.edu/~calc

Professional Activities

Professional Activities

Presentations

  • Dec 2018. International Conference on Big Data and Information Analytics, Houston, TX. Session chair and invited speaker.
  • Sep 2018. Department of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ. Seminar speaker.
  • Jun 2018. ICSA Applied Statistics Symposium, New Brunswick, NJ. Session organizer.
  • Jun 2017. ICSA Applied Statistics Symposium, Chicago, IL. Invited speaker.
  • Dec 2016. Institute of Statistics, Nankai University, Beijing, China. Invited speaker.
  • Dec 2016. Department of Statistics, Central University of Finance and Economics, Beijing, China. Invited speaker.
  • Oct 2016. Georgia Informatics Symposium, Athens, GA. Poster session.
  • Oct 2015. Society of Neuroscience, Chicago, IL. Poster session.
  • Nov 2015. Georgia Statistics Day, Athens, GA. Poster session.
  • Jun 2014. ICSA Applied Statistics Symposium, Portland, OR. Invited speaker.

Referee Services

  • Journal of the American Statistical Association, Statistica Sinica, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Statistical Applications in Genetics and Molecular Biology, Technometrics, Biometrics, Proceedings of the National Academy of Sciences.

Outreach services

  • Nov 2017. Served as a speaker for Speaker Series at The Gwinnett School of Mathematics, Science, and Technology.
  • Apr 2014. Served as a judge for Georgia Science and Engineering Fair.