Yu Wang
About Yu Wang
Yu Wang is a statistician at Procter & Gamble with extensive experience in statistical programming and gene expression analysis.
Title and Current Position
Yu Wang is a Statistician, currently employed at Procter & Gamble in Cincinnati, Ohio, United States. She has been with the company since 2008. Her role involves extensive work in statistical programming, using tools such as SAS, R, and Splus for data manipulation, statistical modeling, data summary, reporting, and visualization.
Previous Experience
Before joining Procter & Gamble, Yu Wang worked as an Engineer at the Institute of Plasma Physics Chinese Academy Of Sciences. Her tenure there lasted from 1992 to 1999, spanning seven years. This early phase of her career laid a robust foundation for her expertise in engineering and scientific analysis.
Education and Degrees Achieved
Yu Wang acquired her Masters in Mathematics and Statistics from the University of Mississippi, where she studied from 2004 to 2007. She previously earned a Bachelors in Materials Science from Shanghai Jiao Tong University in 1970. Her academic background has equipped her with a strong foundation in both the theoretical and practical aspects of statistical analysis and materials science.
Specialization in Statistical Programming
Yu Wang boasts over a decade of experience in statistical programming, particularly proficient in using SAS, R, and Splus. Her expertise lies in data manipulation, statistical modeling, data summary, reporting, and visualization. This extensive experience is pivotal to her current role at Procter & Gamble, where she engages in platform evaluation, study design, quality control, and microarray data analysis, specifically in the field of gene expression.
Focus on Gene Expression and qPCR Experiments
Yu Wang specializes in the design, optimization, validation, and analysis of qPCR experiments. Her work focuses on conducting studies to evaluate new technologies and methods related to microarray platforms. Additionally, she contributes to writing statistical sections in manuscripts and technical reports for clinical and lab studies that relate to consumer goods, demonstrating her capability in both practical experimentation and academic reporting.