We need to be aware of the gender bias and learn how to overcome it. As a female professor, I am confident in my abilities and will not use gender as a judgement.
Dr. Jingjing Wu is an Associate Professor with the Department of Mathematics and Statistics at the University of Calgary. She has a Ph.D. (2008) in Statistics from University of Alberta, a M.Sc. (2002) in Probability from Beijing Normal University, and a B.Sc. (1999) in Computational Mathematics from Minzu University of China. Her PhD thesis was awarded the Pierre-Robillard Award by SSC (Statistical Society of Canada) as the best doctoral thesis in probability or statistics defended at a Canadian University in 2007. Dr. Wu joined University of Calgary in 2007 as an Assistant Professor and was tenured and promoted to Associate Professor in 2013.
Dr. Wu has held Discovery Grants from NSERC since 2008. Her current research is mainly in the area of statistical inferences for semiparametric models and related applications in biostatistics. Minimum distance methods are investigated under both semiparametric model of general form and particularly mixture models, (logistic) regression models and case-control studies. She has keen interests in not only the asymptotic efficiency and robustness properties of minimum distance estimations, but also their applications in survival analysis and genetic studies.
I enjoy the process of exploring and solving research problems with my knowledge and new ideas. I also enjoy supervising my graduate students and I am happy to see them growing and being successful.
My research is in statistics. It is exciting to use statistical methodologies to reveal what is behind the data and what conclusions one can make to provide guidance for the future.
Students who graduate in statistics can enter the workforce as statistician or statistics consultant or data analyst or statistical researcher in industry, government or university.
I think it is important that men and women are equally represented in my field. We need to be aware of the gender bias and learn how to overcome it. As a female professor, I am confident in my abilities and will not use gender as a judgement.
I hope to increase the awareness of bias caused by unequally represented groups and seek specific steps to lessen or remove the bias.
Support programs such as ICAN-WISE scholarships are a great way to encourage females to pursue careers in science and engineering. Activities, such as information sessions and alumni network, particularly designed for females also show an institution’s support.
I have been fortunate to have many role models in my life including my master and PhD supervisors, my teachers and my colleagues. Each of them has something I cherish and can learn from.