Meet McMaster’s new MacDATA Fellows

Using data science to better understand social inequalities in child and youth mental health. Analysing astrophysics data to shed light on the theory of evolution. Using machine learning techniques to assess brain injuries.

Nine McMaster graduate students have been awarded fellowships from McMaster’s MacDATA Institute to pursue these and other multidisciplinary projects that are using data science approaches to provide new insights into a number of areas of research.

Throughout the eight-month fellowship, students will work with McMaster faculty on projects that apply data analysis, collection and curation methodologies to diverse areas of research, including projects related to health care, health policy, finance, biology and linguistics, among others.

“Researchers can get at information they couldn’t get at before because of the richness of the data and the data science methodologies that are being developed,” says Paul McNicholas, director of the MacDATA Institute. “This fellowship provides students with a unique opportunity to work with researchers in other disciplines to apply these methodologies and extract insights from data that might they might not otherwise be able to extract.”

The fellowship is intended to provide students with practical experience, and to facilitate an exchange of knowledge in data science across Faculties. Fellows will be co-supervised by at least two faculty members, who together cover both data science and subject matter expertise. At least one of the supervisors is a member of the MacDATA Institute.

Two of the projects will be completed in collaboration with the Michael G. DeGroote Initiative for Innovation in Healthcare’s (MGDII) Innovation, Commercialization and Entrepreneurship (ICE) program. Experts at the Institute will work with the fellows to identify commercialization opportunities and assist with the development a business plan. It’s part of the Institute’s mandate to increase health innovation within the School of Medicine and the McMaster community.

Learn more about entrepreneurship and commercialization in academia though MGDII workshops and its monthly “Innovators” speaker series. Contact Sarrah Lal for more information.

Meet the New MacData Fellows:

Valentina Antonipillai
How Prescription Drug Coverage affects Health Services Utilization among Immigrants in Canada using Linked Data

Valentina is a Ph.D. student in the Health Policy Program, working under the supervision of Dr. Lisa Schwartz. Her thesis explores how health insurance coverage impacts health service utilization and outcomes of vulnerable populations, such as refugees. Valentina’s MacDATA fellowship is being co-supervised by Dr. Emmanuel Guindon and Dr. Arthur Sweetman. This research will examine how supplementary drug insurance coverage affects health care utilization by immigrants in Canada, combining health research methods, economics, political science and global health disciplines.

Rober Boshra
Automated Brain Injury Assessment- Machine Learning EEG/ERP Analysis

Trained both as a computer scientist (B.Sc., Dalhousie University) and a neuroscientist (M.Sc., McMaster University), Rober’s Ph.D. work in biomedical engineering targets the development of automated assessment tools for brain function. His MacDATA Fellowship will be supervised by Drs. John Connolly and James Reilly. He will utilize machine learning techniques to analyze brain signals, recorded using electroencephalography (EEG), to assess brain injury and its effects on different aspects of cognition. This project is funded in part by the Michael G. DeGroote Initiative for Innovation in Healthcare.

Yicheng Chen
Machine Learning and Bayesian Inference in Finance

Yicheng is a Master’s student at the School of Computational Science and Engineering, with a focus on machine learning, finance, and economics. His supervisors for the MacData fellowship are Dr. Matheus Grasselli and Dr. Sonia Anand. Yicheng’s research will focus on how to apply machine learning techniques to finance, with some focus on the impact of capital markets. In other words, he will study how to grasp the complexity of machine learning applications with regards to investments. For this project, he will use Bayesian methods to calibrate his work for option pricing.

Michael Gallaugher
Analysis of Social Inequalities in Child and Youth Mental Health

Michael is a second year Ph.D. student and Vanier Scholar in the Department of Mathematics and Statistics working under the supervision of Dr. Paul McNicholas. Recently, he has been looking at developing methodology for an important data science problem, i.e., the analysis of three way data. During of the course of this fellowship, which will be co-supervised by Dr. Kathy Georgiades, Michael plans to apply clustering and classification techniques to better understand social inequalities in child and youth mental health and associated academic outcomes, specifically in migrant groups.

Sophiya Garasia
Senior Immigrant Health in Ontario

Sophiya Garasia is a Ph.D. student in the Health Policy Ph.D. program at McMaster University in the Health Economics stream. Her research interests lie in areas of health equity, health economics and quantitative methodology. Sophiya’s MacDATA project, which will be supervised by Emmanuel Guindon, Arthur Sweetman and Kathy Georgiades, focuses on health care outcomes and health care utilization trends in immigrant seniors compared to Canadian-born seniors. Data will be obtained from multiple cycles of the Canadian Community Health Survey (from 2000 to 2015) and linked to a number of datasets. The results of this research could have implications for decision making in the areas of ethno-specific long-term care in Ontario and immigration and social policies targeted toward immigrant seniors.

Regina Kampo
Analyzing Astrophysics Data using Machine Learning Techniques

Regina is currently a Ph.D. student in the School of Computational Science and Engineering at McMaster University. Prior to coming to McMaster University to take an MSc in Statistics, she obtained an Honours BSc in Mathematics and Statistics from the University of Ghana. Her Ph.D. is focused on developing evolutionary algorithms, where some elements of the biological theory of evolution are incorporated into computer algorithms. Regina’s MacDATA fellowship will be supervised by Dr. Sharon McNicholas and Dr. Laura Parker, and will focus on using statistical learning techniques to shed light on some problems in astrophysics.

Bryor Snefjella
Massive Multilingual Semantic Norm Extrapolation

Bryor Snefjella is Ph.D. student at McMaster University, in the Cognitive Science of Language program, with interests in corpus linguistics, quantitative linguistics, psychology, and psycholinguistics.  His MacDATA fellowship will be supervised by . Drs. Victor Kuperman and Louis Schmidt. He uses corpora(searchable databases of language samples for linguistic research), including representative academic corpora, social media, and other sources, to examine how the sensorimotor and affective connotations of words affect language processing, and reflect how we mentally represent people, events, and places.

Damian Tran
Artificial Intelligence Algorithms for the Discovery of Novel Therapeutics for Acute Myeloid Leukemia

Damian is an MSc. student in the Faculty of Health Sciences at McMaster University, working in the Hope Cancer Lab at the Stem Cell and Cancer Research Institute (SCC-RI). His MacDATA fellowship will be supervised by Drs. Kristin Hope and Andrew McArthur. Damian’s research focuses on the development of an Artificial Intelligence (AI) program that has been able to discover possible approaches to targeting the speculated driver cells of Acute Myeloid Leukemia (AML).  This project endeavours to expand upon this AI’s abilities to allow it to sift through the volumes of literature in fields of medicine, biochemistry and pharmacology published online in order to create self-updating data repositories for pharmaceutical repurposing.This project is funded in part by the Michael G. DeGroote Initiative for Innovation in Healthcare.

Yongyong Wei
Big Data in Business Strategic Decisions ─ An Application in Gas Station Prices

Yongyong is a Ph.D. student in the Department of Computing and Software under the supervision of Dr. Rong Zheng. His MacDATA fellowship will be  co-supervised by Dr. Ruhai Wu from the DeGroote School of Business.  The fellowship project will analyze gasoline prices and create a data-driven decision support system for gas station pricing. The purpose is to develop a tool that will collect data on gas pricing and, using advanced algorithms, analyse the data and ultimately create an optimal pricing model to guide gas stations in improving their pricing decisions.

The fellowship program is part of the MacData Institute’s mission to promote and support the engagement of researchers and students within McMaster as well as externally with industry, government and the community to strengthen McMaster’s position as an international leader on all matters related to data.