Nicholas Grubic (he/him) is a dedicated PhD student in Epidemiology at the prestigious Dalla Lana School of Public Health. His diverse research interests encompass cardiovascular epidemiology, mental health, sudden cardia arrest, health administrative data, and advanced statistical methodologies, Prior to his current academic pursuit, Nicholas garnered valuable experience through roles at ICES, Ontario Health, and Broadstreet HEOR. ​

Nicholas’ academic journey includes an M.Sc. in Epidemiology, a B.Sc. in Life Science, and a Certificate in Business, all from Queen’s University. Within the Ge-iSESS lab, Nicholas has contributed significantly as a Research Assistant under the guidance of Dr. Erjia Ge and Dr. Sara Brode, actively participating in multiple research initiatives. Notably, he has been instrumental in projects such as the CIHR-funded Greenness Accessibility and Asthma Project, the Air Pollution and TB Progressions Project, and the Environmental Exposure and COVID-19 Project. ​

His extensive expertise in statistical analyses and disease modeling has culminated in the publication of over 30 peer-reviewed papers. To delve deeper into Nicholas’s prolific body of work, please visit his Google Scholar  and  PubMed page. For inquires or collaboration opportunities, you can reach him at nicholas.grubic@utoronto.ca. ​

Nicholas Grubic’s recent publications:
Grubic, N., Hill, B., Allan, K. S., Dainty, K. N., Johri, A. M., & Brooks, S. C. (2023). Community Interventions for Out-of-Hospital Cardiac Arrest in Resource-Limited Settings: A Scoping Review Across Low, Middle, and High-Income Countries. Prehospital Emergency Care, 1–13. Advance online publication. https://doi.org/10.1080/10903127.2023.2231559
Hussain, J., Grubic, N., Akbari, A., Canney, M., Elliott, M. J., Ravani, P., Tanuseputro, P., Clark, E. G., Hundemer, G. L., Ramsay, T., Tangri, N., Knoll, G. A., & Sood, M. M. (2023). Associations between modest reductions in kidney function and adverse outcomes in young adults: retrospective, population based cohort study. British Medical Journal, 381, e075062. https://doi.org/10.1136/bmj-2023-075062
Grubic, N., Allan, K. S., Drezner, J. A., Hill, B., & Johri, A. M. (2023). Public emotions and opinions following the sudden cardiac arrest of a young athlete: A sentiment analysis. The American journal of emergency medicine, 67, 179–181. https://doi.org/10.1016/j.ajem.2023.03.015
Grubic, N., Peng, Y. P., Walker, M., Brooks, S. C., & CARES Surveillance Group (2022). Bystander-initiated cardiopulmonary resuscitation and automated external defibrillator use after out-of-hospital cardiac arrest: Uncovering disparities in care and survival across the urban-rural spectrum. Resuscitation, 175, 150–158. https://doi.org/10.1016/j.resuscitation.2022.04.014

Joey (Zhou) Zang (he/him) is a dedicated PhD student under the guidance of Dr. Jane Liu within the Department of Geography and Planning at the University of Toronto. His journey with the Ge-iSEE lab began as a student research assistant, where he played a pivotal role in the department of advanced geospatial models aimed at enhancing the measurement of air pollution and meteorological factors. This work holds significant importance, as it lays the foundation for robust data and establishes an accessible repository crucial for a wide range of environmental epidemiological studies.​​

Joey’s doctoral research is centered around the long-term tropospheric ozone climatology on a global scale. To tackle this intricate topic, he employs a multitude of innovative techniques, including remote sensing, modeling and statistical approaches. Through these methodologies, Joey endeavors to unravel the trends in tropospheric ozone and understand how it is impacted by climate change. Read more about Joey’s work on Google Scholar page.​

Joey Zang’s recent publications:
Yan, X., Zang, Z., Li, Z., Luo, N., Zuo, C., Jiang, Y., Li, D., Guo, Y., Zhao, W., Shi, W., and Cribb, M.: A global land aerosol fine-mode fraction dataset (2001–2020) retrieved from MODIS using hybrid physical and deep learning approaches, Earth System Science Data, 14, 1193–1213, 2022.
Zang, Z., Guo, Y., Jiang, Y., Chen, Z., Li, D., Shi, W. and Yan, X. (2021). Tree-Based Ensemble Deep Learning Model for Spatiotemporal Surface Ozone (O3) Prediction and Interpretation. International Journal of Applied Earth Observation and Geoinformation, 103, 102516.
Zang, Z., Li, D., Guo, Y., Shi, W. and Yan, X. (2021). Superior PM2.5 estimation by integrating aerosol fine mode data from the Himawari-8 satellite in deep and classical machine learning models. Remote Sensing, 13(14), 2779.

Andrea Portt (she/her), a driven PhD student specializing in Epidemiology at the University of Toronto. Her research passion lies in deciphering the profound impact of environmental exposures on neurological health. Under the mentorship of  Dr. Peter Smith, Andrea’s doctoral journal journey is focused on the innovative use of mobile app data to unravel the intricate link between air pollution and migraines. ​

Her work is not just academically relevant but has the potential to provide valuable insights into the everyday health experiences of individuals. To delve deeper into Andrea’s compelling research, please read more Read more about Andrea’s work on her Google Scholar page. For inquiries or collaboration collaboration opportunities, feel free to connect with her through email at: andrea.port@mail.utoronto.ca. 

Russell Forrest

[under development]