Research Portal on Machine Learning for Social and Health Policies

The portal (MLPortal) provides a hub for researchers who want to make machine learning methods more accessible in social and health science applications for better predictive and causal analyses. We hope to offer a platform for statistical learning by enhancing collaboration between academic circles, policy makers, and private enterprises by disseminating the knowledge that helps others in their works, projects, course offerings, and private applications.

In 2018, in collaboration with two of my colleagues, I co-founded MLPortal. Under the umbrella of this research portal, we currently have ten researchers actively working on subjects that range from the prediction of chronic diseases using better surveillance systems to issues related to the design of a better selection process for immigration policies by providing policy makers with a recommender system.
Research Portal on Machine Learning for Social and Health Policies

Events

2nd Workshop of Applied Microeconomics

(In-person & Online - August 10-11, 2023, Halifax)

1st Workshop of Applied Microeconomics

(In-person & Online - August 24-25, 2022, Halifax)

Summer School on Machine Learning for Economists

(Online - July 20, 21, 22 - 2020)
As an applied economist, or researcher in a related field, if you feel that you need to learn these contemporary machine learning methods, implement them into your research, or looking for articles applied these methods to incorporate into the courses that you are teaching, this course is for you. In this course, participants will learn the fundamentals of machine learning and their implementation, recalling the fundamental statistical concepts at the heart of modern learning techniques. Participants will learn the differences between causal and predictive analyses and their relative merits, as well as their use in applied social sciences.

The course will combine both real data and theoretical background to enable researchers to gain practical experience in analysing a wide variety of data and econometric problems. It will also discuss how contemporary approaches in applied econometrics can be used to answer important questions in Economics. Participants will be provided a wealth of research papers and sources which apply the techniques being taught. Applications covered during the course will include the fields of labour, development, industrial organisation, health, macro economics and finance.

Webinar on Machine Learning for Economists

(Online - July 20, 23, 24 - 2020) The purpose of this webinars is to share the latest applications of machine learning methods in different fields. These webinar series will be free and open to all researchers around the world