MPS Policy and Data Lab


The primary objective of the Master of Public Service’s Policy & Data Lab (‘The Lab’) is to conduct and encourage data oriented research on a wide array of emerging public policy issues that are important to Canada. This is accomplished through developing and creating interdisciplinary research partnerships between faculty and graduate students across the University of Waterloo, as well as with the university’s international partners. The Lab is particularly interested in encouraging research that uses complex statistical methods to conduct behavioural analysis of government policies.    

The Lab also organizes an annual Datafest where graduate students from across the university, compete to produce compelling data based analyses of problems recommended by different government organizations. Videos of student presentations from previous competitions can be found on University of Waterloo's Faculty of Arts YouTube channel.     

Another goal of The Lab is to communicate findings from published research in academic journals through blogs and podcasts. By doing this, The Lab aims to bridge the gap between academic research and policy formulation, and build enhanced awareness of scientific developments and public confidence in policy decisions.


The University of Waterloo is the epicentre for disruptive advancements in the science, technology, engineering, and mathematics (STEM) fields. The research emerging from Artificial Intelligence (AI) and Big Data are making real-world impacts on scientific knowledge and advancements, new types of businesses, innovative products, and exciting labour market opportunities.

However, there continues to be limited attention on the spillover effects that these disruptive innovations can have in terms of public policy, equity and economic outcomes. Ignoring these implications might have the effect of worsening the digital divide and lead to unintended consequences that adversely impact society. Further, a majority of AI and Big Data related research is focused on implications for industry, rather than on opportunities for government and public policy. 

Our People

Anindya Sen - Lab Director

Anindya Sen is a professor at the Department of Economics and is the current director of Master of the Public Service program. His published research has also focused on assessing the empirical impacts of a wide variety of policies, such as stricter impaired driving laws, mandatory seatbelt legislation, cigarette taxes, and the minimum wage. Professor Sen’s current research interests are in the use of Big Data/Machine Learning methods to study the relationships between individual choices, societal outcomes, and public policy.

Allison Mascella, Research Associate

  • B-Comm Economics and Management Science Ryerson University
  • MA International Economics and Finance Ryerson University
  • PhD Applied Economics (expected 2020)

Allison is a doctoral student in the Department of Economics at the University of Waterloo. She has published research on the relationship between higher minimum wages and poverty alleviation. Her current research interests are in the use of advanced statistical methods to study cultural differences in trade-offs between income and time spent with children, and difference in wages earned by minority groups.

Leah Connor, Research Associate

Leah Connor holds a Bachelor of Arts (Hons.) in Social Development Studies with specializations in both Policy and Social Work. She completed her Master of Public Service at the University of Waterloo. Leah has experience in municipal government as an Economic Researcher. She was a Teaching Assistant and a Research Apprentice at Renison University College. Leah is currently on the Community Editorial Board for the Waterloo Region Record where she writes about contemporary diversity issues within her community.


Guest Topic Host(s)
Joel Blit; Associate Professor, Economics, University of Waterloo Covid and its impact on work and automation Prof. Anindya Sen and Leah Connor


Virtual Conference - What Needs to be done in order to curb the spread of Covid-19: Contact tracing, legal considerations, and statistical modeling