Qing (Wendy) Wang

Associate Professor of Mathematics

Contact
Phone:
+1 (781) 283-3397
Email:
qwang@wellesley.edu
Department
Mathematics & Statistics
Data Science

Links

Statistician specializing in topics of U-statistics, nonparametric kernel density estimation, risk estimation, variance estimation, cross-validation, resampling schemes, and extrapolation/interpolation methods.

I was born and raised in Beijing, China. My academic journey in the U.S. began in 2007 when I started the PhD program in statistics at Penn State University. I completed my PhD at Penn State in 2012 under the supervision of the late Dr. Bruce G. Lindsay. Prior to joining Wellesley, I held tenure-track Assistant Professor of Statistics positions at Williams College (2012–2015) and Bentley University (2015–2016).

My research centers on topics in U-statistics, risk and variance estimation, and cross-validation. My current research interests also include penalization methods, model assessment tools, high-dimensional mediation analysis, jackknife empirical likelihood, and multilabel classification.

I teach both applied and theoretical statistics courses, including Introductory Statistics, Regression Analysis, Probability, Multivariate Data Analysis, Nonparametric Statistics, and Bayesian Statistics. As one of the data science advisors, I also rotate to teach the data science senior capstone course. I deeply enjoy mentoring undergraduate students on research projects and have a solid and growing record of publications with undergraduate co-authors. I also have a great passion for undergraduate statistics education, and I’m actively involved in developing and incorporating active-learning educational tools in my classroom teaching.

Outside of my academic life, I enjoy baking, cooking, practicing yoga, traveling with my husband, and spending time with my two lovely children, Iwa and Ian.

Education

  • B.S., Beijing Normal University (北京师范大学)
  • M.S., Pennsylvania State University-Main Campus
  • Ph.D., Pennsylvania State University-Main Campus

Current and upcoming courses

Capstone in Data Science

DS340H

Senior data science majors enroll in this course in order to meet the major’s capstone requirement. The goal is to integrate and solidify the concepts learned in previous major courses. Students will demonstrate the ability to conduct applied projects via the steps in the data science process. Students will complete the capstone with the critical thinking needed to pose and refine questions that can be answered with data in an ethical way; the statistical skills needed to draw meaning from data appropriately; the computational skills needed to tackle practical data challenges; and the ability to collaborate, communicate, and critique in the context of modern data. The course is also a chance to practice and demonstrate key technical skills, such as code sharing on github or a strong command of data science libraries in both Python and R. At the end of the course, students will have created a project or portfolio that can be shared publicly. The course must be taken for a letter grade.