Having recently completed his PhD in Biostatistics at the University of Minnesota, Jun Young Park joined the University of Toronto’s Department of Statistical Sciences and the Department of Psychology as an assistant professor in July 2020. Jun’s research interests include modelling correlated data and applying resampling for statistical inference. As an applied statistician, he expects to contribute to science through collaborations with faculty, students, and researchers. His work has been recognized with student paper awards from the Statistics in Imaging section of American Statistical Associations in 2019 and 2020.
U of T Statistical Sciences: Welcome to the StatsSci team and congrats on your new role! What got you interested in U of T and the Stats Department?
U of T was undoubtedly the perfect option for me. The most important factor was that the university and the department keeps growing rapidly. Also, as an applied statistician, I needed to see how many collaborative opportunities I would be able to pursue, and there are many world-class researchers whose research areas are relevant to mine. I am delighted to start the next stage of my academic career at U of T.
You have a fascinating international background! Can you tell us more?
I was born in Seoul, South Korea, and lived there for 20 years. Pursuing an undergraduate degree in the United States was daunting because there were expected and unexpected challenges I needed to face. Language is an obvious one, and the college was in a small town, which I liked in the end. But it was different from what I imagined before coming to the United States. Yet, I ended up staying in Minnesota for my graduate studies, and I felt that my time there was valuable to me. In graduate school, I was fortunate to work with different faculty on different topics, which broadened my research interests and, ultimately, motivated me to pursue a career in academica. And, of course, freezing weather in Minnesota prepared me for survival in Toronto!
Yes, Toronto! What are you most looking forward to about life in Toronto?
I am delighted to have such an excellent opportunity to live in Toronto! However, the COVID-19 pandemic has affected everyone, and my time in Toronto has started with two weeks of self-quarantining. At some point, I look forward to exploring the many good restaurants Toronto has to offer, and visiting the Rogers Centre to watch the Blue Jays .
U of T was undoubtedly the perfect option for me. […] The department keeps growing rapidly, […] and there are many world-class researchers whose research areas are relevant to mine.
Which statistics courses will you be teaching?
This Fall, I will be teaching STA1008H: Applied Statistics. This course had been discontinued for a number of years, and I’ve been working on the course designs and materials to provide statistical insights and make students interested in applied data analysis. I believe this course will be an excellent opportunity for non-statistics graduate students using statistics in their research.
You will be cross-appointed with the Department of Psychology. How do these disciplines intersect for you and within your research?
Jesse Gronsbell, whom you interviewed previously, mentioned the famous quote by John Tukey: “The best thing about being a statistician is that you get to play in everyone’s backyard.” I also like this quote. Study designs and data types used in psychology are often very interesting and yield research questions that statistics can play an important role in. My previous research is connected with different fields of psychology, including neuroimaging (MRI/fMRI) and family studies in genetics. I enjoy collaborating with researchers and reading related papers to dig out potential research topics. I am happy to be appointed by both departments, and I seek to expand my research spectrum in the future.
Understanding the mechanism of the human brain and its relationship with cognition and neurodegenerative diseases is an active area of research. […] As a statistician, I develop statistical models and inference procedures to better understand the brain and provide new insights.
Regarding your work in fields like neuroimaging and genetics: can you tell us more about that?
Understanding the mechanism of the human brain and its relationship with cognition and neurodegenerative diseases is an active area of research. Studies of the human brain have various types of study designs and provide several data types including, but not limited to, functional/structural magnetic resonance imaging (fMRI/sMRI), electroencephalogram (EEG), and positron emission tomography (PET). Neuroimaging data is often “big” and complex, and it yields several layers of correlation structures that statistics need to account for to improve our understanding of the human brain. It is also a growing field, and the increase in interest in the role of genetics on the brain has led to the birth of an entirely new field called imaging genetics. As a statistician, I develop statistical models and inference procedures to better understand the brain and provide new insights.
Any other current research interests?
My current research interests are several folds, but I am primarily interested in using neuroimaging and genetics data to study brain-related phenotypes. Current studies in neuroimaging use large-scale cohort studies and have numerous imaging databases, such as the UK Biobank and the ABCD study, to name a few. In addition to the high dimensionality of the data, there is a growing interest in integrating multiple data types in a useful and meaningful way to bring new perspectives on cognitions and brain disorders. However, there are other interesting topics I am interested in, such as mediation analysis or chemometrics. I am open to any statistical method if it can bring new, useful insights.
[…] I hope to provide the best environment for students who are interested in statistics and research. […] I am eager to advise students with passion and respect and teach statistics courses in a motivating way so that no one is left behind.
What do you hope to accomplish in your tenure at U of T?
First, I hope to provide the best environment for students who are interested in statistics and research. The decision to spend a number of years at the University of Toronto will be a life-changing one to students, and I want them to achieve their primary goals at the time of graduation. My time in graduate school was not boring or exhausting because colleagues and advisors always cheered me up. I am eager to advise students with passion and respect and teach statistics courses in a motivating way so that no one is left behind.
Second, I also expect my decision to join U of T to be life-changing. It is an excellent opportunity for me, and I am motivated to collaborate with faculty and students on interesting topics.
Do you have some fun facts about yourself you could share?
When I was young, I decided not to become a medical doctor or nurse because I hated vaccinations and injections. I eventually turned out to be a combat medic when I served two years in the military in South Korea, and I did a pretty good job!
© 2020 U of T Statistical Sciences