HI I’M YIWANG ZHOU
EDUCATION
September 2017 - Expected 2021
PH.D. UNIVERSITY OF MICHIGAN
BIOSTATISTICS
September 2015 - April 2017
M.S. UNIVERSITY OF MICHIGAN
BIOSTATISTICS
September 2012Â - March 2015
M.S. UNIVERSITY OF TORONTO
MOLECULAR GENETICS
September 2008Â - June 2012
B.S. PEKING UNIVERSITY
BIOLOGICAL SCIENCES
RESEARCH
My CV is available for download here.
GRADUATE METHODS RESEARCH, UNIVERSITY OF MICHIGAN
I joined the Song Lab group for my doctoral dissertation research in statistical methods in the Summer of 2017. My thesis work focuses on the derivation of individualized treatment rules (ITRs) in precision medicine. Specifically, I developed a new biomarker assessing procedure called Net Benefit Index (NBI) in the establishment of ITRs, and proposed a synergistic self-learning (SS-learning) method in deriving ITRs by incorporating multiple benefit outcomes with heterogenous qualities and clinical relevance.
GRADUATE APPLIED RESEARCH, UNIVERSITY OF MICHIGAN
From 2018 to 2019, I worked with Professor Peter Song exploring associations between long-term exposure to PM2.5 and the 5-year graft failure rate for kidney transplant recipients in the USA. During 2017 to 2018, I worked for Professor Ivo Dinov as a research assistant in the Statistics Online Computational Resource of the University of Michigan. My work primarily focused on the predictive Big Data analysis of the associations between neuroimaging biomarkers and mental disorders using the UK Biobank Data. In 2016 and 2017, I collaborated with Professor Bin Nan and Professor Sioban Harlow in the Michigan Bone Health and Metabolism Study for the analysis of women's decline einstradiol.
GRADUATE RESEARCH, UNIVERSITY OF TORONTO
From 2012 to 2015, I completed a M.S. research project in proteomic analysis of PP2A mutants and PP2A-related tumor virus proteins with Professor Anne-Claude Gingras from University of Toronto.
UNDERGRADUATE RESEARCH, PEKING UNIVERSITY
From 2010 to 2012, I completed a research project in the screening of the binding partners of CSDP1 in Arabidopsis thaliana by phage display with Professor Lijia Qu from Peking University.
PUBLICATIONS
PEER-REVIEWED JOURNAL ARTICLES
1. Zhou, Y., Zhao, L., Zhou, N., Zhao, Y., Marino, S., Wang, T., Sun, H., Toga, A.W. and Dinov, I.D., 2019. Predictive Big Data Analytics using the UK Biobank Data. Scientific reports, 9(1), p.6012.
2. Marino, S., Xu, J., Zhao, Y., Zhou, N., Zhou, Y. and Dinov, I.D., 2018. Controlled feature selection and compressive big data analytics: Applications to biomedical and health studies. PloS one, 13(8), p.e0202674.
3. Mui, M.Z., Zhou, Y., Blanchette, P., Chughtai, N., Knight, J.F., Gruosso, T., Papadakis, A.I., Huang, S., Park, M., Gingras, A.C. and Branton, P.E., 2015. The human adenovirus type 5 E4orf4 protein targets two phosphatase regulators of the Hippo signaling pathway. Journal of virology, 89(17), pp.8855-8870.
4. Zhou, Y., Song, P.X., and Fu, H. Net Benet Index: Assessing the Influence of a Biomarker for Individualized Treatment Rules. (Under review)
5. Marino, S., Zhao, Y., Zhou, N., Zhou, Y., Toga, A.W., Zhao, L., Jian, Y., Yang, Y., Chen, Y., Wu, Q., Wild, J., Cummings, B., and Dinov, I.D. Compressive Big Data Analytics: An Ensemble Meta-Algorithm for High-dimensional Multisource Datasets. (Under review)
6. Zhou, Y., and Song, P.X. Synergistic Self-learning of Individualized Dietary Supplement Rules from Multiple Health Benefit Outcomes. (In preparation)
7. Zhou, Y., Luo, S., Homan, K., and Song, P.X. Particulate Matter Air Pollution and the Risk of Graft Failure Among Kidney Transplant Recipients. (In preparation)
8. Harlow, S.D., Nan, B., Zhou, Y., Karvonen-Gutierrez, C., McConnell, D., Zheng, H. and Randolph, J.F. Decline in Estradiol denes Duration of the STRAW+10 Stages of Postmenopause; The Michigan Bone Health and Metabolism Study. (In preparation)
ORAL PRESENTATIONS
1. Synergistic Self-learning of Individualized Dietary Supplement Rules from Multiple Health Benefit Outcomes. University of Michigan Department of Statistics Student Seminar, Ann Arbor, MI. October 2019.
2. Net Benefit Index: Assessing the Influence of a Biomarker for Individualized Treatment Rules. International Biometrics Society ENAR Spring Meeting, Philadelphia, PA. March 2019.
POSTER PRESENTATIONS
1. Net Benefit Index: Assessing the Influence of a Biomarker for Individualized Treatment Rules. Michigan Student Symposium for Interdisciplinary Statistical Sciences (MSSISS), Ann Arbor, MI. March 2019.Â
2. Biomarker Screening in the Derivation of Individualized Treatment Rules via Net Benefit Index. Women in Big Data at Michigan Symposium, Ann Arbor, MI. November 2018.Â
3. Biomarker Screening in the Derivation of Individualized Treatment Rules via Net Benefit Index. Statistical and Computational Challenges in Precision Medicine Workshop, Minneapolis, MN. November 2018.
4. Biomarker Screening in the Derivation of Individualized Treatment Rules via Net Benefit Index. Michigan Institute for Data Science (MIDAS), Ann Arbor, MI. October 2018.
5. Predictive Big Data Analytics using the UK Biobank Data. Joint Statistical Meetings (JSM), Vancouver, BC, Canada. August 2018.
6. Rapid mapping of PPP2R1A interactomes by AP-SWATH. Canadian National Proteomics Network (CNPN), Vancouver, BC, Canada. April 2013.
ABOUT ME
I am now a Ph.D. candidate in the Department of Biostatistics at the University of Michigan. I have been in Ann Arbor for over four years and really enjoy living in this beautiful small town. I was born in Kunshan, China, and lived four years in Beijing, China for my undergraduate. Then I moved to Toronto, Canada, where I pursued a M.S. degree in Molecular Genetics. I have a beautiful cat named Hapi who is 3 years old now. You can find her in the following photos. I love to travel. Recent trips include Blue Mountain at Canada, Cape Cod, Glacier National Park, Upper Peninsula of Michigan.