Who We Are

Applied Statistics and Data Science (ASDa) is the research support and general statistical consulting group of the Department of Statistics at the University of British Columbia.

By applying best practices and capitalizing on our working relationships with leading data science researchers, our professional statistical consultants and scientific programmers can help you with all of your data analytics needs. For example, ASDa can:

Our History

Statistical Consulting and Research Lab (SCARL) was created shortly after the Department of Statistics was created in 1983. The vision was a research support unit for the Department of Statistics, to include computing, programming, data analysis, and statistical modeling. Over the years, demand from outside the department developed and it was accommodated on a user fee basis.

Starting in 2014, we began work on the new vision for the lab, in response to the emergence of data science and within it data analytics, with big data and high dimensional data analysis as fundamental features. Out of the consulation with the department researchers, our partners, and other stakeholders, SCARL was redeveloped as ASDa. The new name more accurately reflects our expertise, and the new vision for the group expands its horizon to be the leader in practical data science at UBC and the region.

Our Team

Rollin Brant

Rollin is a professor in the Department of Statistics and the faculty supervisor of ASDa.

Carolyn Taylor

Carolyn currently is the Managing Consultant for ASDa and has served as a statistical consultant in the Department of Statistics since completing her MSc degree in Statistics at SFU in 1998. She works with Statistics professors, Industry research partners and Government agencies on problem formulation, study design, data management, method development, analysis and implementation. She continues to support investigators and students on the second of two 5-year industry collaborative research and development grants.

Biljana Jonoska Stojkova

Biljana is a statistical consultant with ASDa, providing support for investigators on various research grants. She has recently completed her PhD in Statistics at SFU, where she focused on developing Bayesian algorithms and methods for multi-modal posterior spaces which were applied to differential equation models, mixture Gaussian models and ecological models. In collaboration with tech industry and the Mitacs Accelerate program, she applied probabilistic models to determine different patterns of user behavior from chat messages. In the previous roles she has gained experience with development of relational databases and with machine learning algorithms such as supervised and unsupervised learning.