Four graduate students have received fellowships from McMaster’s MacDATA Institute to pursue interdisciplinary projects that apply data analysis, collection and curation methodologies to a number of areas. These include a scholarly exploration of research on antimicrobial resistance and the potential for low-risk cryptocurrency market investment.
New and innovative data science methodologies are allowing researchers to get more from their data than ever before, says Paul McNicholas, director of the MacData Institute and Tier 1 Canada Research Chair in Computational Statistics.
“This fellowship brings together students and researchers from all faculties to approach data analysis in novel ways – ways that are helping to reveal new insights from increasingly complex data.”
Each fellow is co-supervised by at least two faculty members who, together, cover data analytics and subject matter expertise. At least one of the supervisors is a member of the MacDATA Institute.
The fellowship program is part of the MacData Institute’s mission to promote innovative research and training programs related to data science, and to work with and support faculties and institutes on data issues and initiatives.
The new MacDATA fellows are:
Zhe (Betty) Ji
Zhe (Betty) Ji
Reimagining Canadian Real Estate Market: Lead Generation and Transaction Outcome Forecast with Data Analytics
Business administration PhD student Zhe Ji is developing data analytics solutions to help real estate agents improve data-driven strategic decision-making in the rapidly digitizing landscape of the Canadian real estate market.
Supervisors: Ruhai Wu and Rong Zheng
Hamidreza Masoumi
Hamidreza Masoumi
Is a low-risk investment possible in cryptocurrency markets?
DeGroote School of Business Finance PhD candidate Hamidreza Masoumi will explore viable pathways for low-risk investment in cryptocurrency markets. His goal is to devise a market-neutral investment strategy as a low-risk approach for investing in cryptocurrencies via analysis of high-frequency financial data, exploring avenues to develop a portfolio that is neutral to overall market risk through tracking measures that can capture risk characteristics of cryptocurrencies.
Supervisors: John Maheu and Noah Forman
Michael De Coste
Michael De Coste
Prediction of Spring Breakup of River Ice Cover on a National Scale using Canada-Wide River Ice and Climate Data
Civil engineering PhD candidate Michael De Coste is studying river ice breakup – a yearly event on many Canadian rivers – as an indicator of climate variability. His goal is to use long-lead time forecasts about the timing of spring breakup to provide early warning to flood prone communities and to analyze how these events will change in response to climate change.
Supervisors: Zoe Li and Ridha Khedri
Arman Edalatmand
Arman Edalatmand
Identifying gaps and biases in antimicrobial resistance research through peer-reviewed literature analysis
Arman Edalatmand is a master’s student in biochemistry and biomedical sciences in the Faculty of Health Sciences. He will explore gaps in the massive repository of research on antimicrobial resistance, using scholarly publication data. His goal is to explore whether AMR research is evenly represented across the world; what areas of research are being explored in the field; and, of these which drive the field and which are understudied. This work would reveal the biases in the field and give insight into areas needing further exploration.
Supervisors: Andrew McArthur and Victor Kuperman