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Liaison Newsletter

We in the Department of Statistics at the University of British Columbia (UBC) are thrilled to be welcoming the following five new faculty colleagues: Vincenzo Coia, Melissa Lee, Rodolfo Lourenzutti, Daniel McDonald, and Yongjin Park.

Rodolfo, Melissa, and Vincenzo took up assistant professor of teaching positions with us on July 1.

On the same date, Daniel joined us in an associate professor.

And Yongjin will begin his role as an assistant professor in a joint position between the Department of Pathology and Laboratory Medicine and the Department of Statistics on September 1.

We’re excited by this imminent infusion of talent, and we’re looking forward to working with our incoming colleagues, some of whom are actually familiar faces in our department.  

Get to know our new colleagues

Vincenzo Coia

Vincenzo began an assistant professor of teaching position with us on July 1.

After completing his PhD in Statistics at UBC, Vincenzo continued contributing to the department by teaching, first as a postdoctoral teaching and learning fellow and then as a lecturer, jointly with the UBC Master of Data Science (MDS) program.

Vincenzo is focused on developing data science initiatives at UBC. He focused on developing and delivering the MDS program at UBC during its first four years, and now he is working with his colleagues to develop a new Data Science minor program at UBC.

In addition to his teaching and course development, Vincenzo also has experience as a flood forecasting consultant.

He likes to make his work public, much of which you can find from his website.

 

 

 

 

Melissa Lee

Melissa began an assistant professor of teaching position with us on July 1.

After receiving her MSc in Statistics at UBC, Melissa has continued to be very active in the department and the broader statistics community. In addition to teaching introductory statistics, Melissa is dedicated to improving statistics education for instructors and learners.

Notably, she has contributed to projects that develop resources that advance statistics education. One of these projects is the Flexible Learning in Statistics Project, where she has been heavily involved in the development and maintenance of an open-education-resources repository called StatSpace. She has also led or supported several course development or renewal projects.

Most recently, Melissa worked with a team to develop course material for UBC’s first undergraduate data science course, DSCI 100 (Introduction to Data Science).

 

 

 

Rodolfo Lourenzutti

Rodolfo began an assistant professor of teaching position with us on July 1.

Rodolfo is coming from a position as a postdoctoral teaching and learning fellow in UBC’s Master of Data Science (MDS) program.

Originally from Vila Velha, a coastal town in Brazil, Rodolfo Lourenzutti has a long-standing passion for data analysis, which drove him to pursue a BSc and MSc in Statistics. For his PhD, Rodolfo switched fields to computer science, in which he obtained a PhD from the Federal University of Espírito Santo.

During his PhD, he spent 10 months working at the Department of Electrical and Computer Engineering at the University of Alberta. After completing his doctorate, he worked as a postdoctoral fellow at the University of Alberta in the Department of Civil & Environmental Engineering.

 

 

 

Daniel McDonald

Daniel began an associate professor position with us on July 1.

Before moving north, Daniel spent eight years on the faculty at Indiana University, Bloomington. His research interests involve the estimation and quantification of prediction risk, especially developing methods for evaluating the predictive abilities of complex dependent data. This includes the application of statistical learning techniques to time series prediction problems in the context of economic forecasting, as well as investigations of cross-validation and the bootstrap for risk estimation.

Daniel did his undergraduate studies at Indiana University, where he received two bachelor’s degrees: a Bachelor of Science in Music with a concentration in cello performance from the Jacobs School of Music and a Bachelor of Arts in Economics and Mathematics. He received his PhD from Carnegie Mellon University in Statistics.

 

 

 

 

Yongjin Park

Yongjin will begin his role as an assistant professor in a joint position between the Department of Pathology and Laboratory Medicine and the Department of Statistics on September 1.

Yongjin is a machine learning researcher who can speak genomics and network science. His research primarily focuses on developing scalable probabilistic inference methods to elucidate hidden causal mechanisms of human diseases, such as cancer and other common/complex disorders.

He was previously a research scientist in Computer Science and Artificial Intelligence Laboratory at MIT, working on a causal inference problem of statistical genetics. He received a BSc in Biology and Computer Science and Engineering from Seoul National University, an MSc in Computational Biology from Carnegie Mellon University, and a PhD in Biomedical Engineering from Johns Hopkins University.

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