Course Detail: STAT340 - Data Science Methods in Epidemiology - COVID-19 - NEW!
This course aims at learning, understanding, and discussing several topics related to epidemiology and specifically the COVID-19 pandemic. The main tools we will use will dig into Data Analysis at different levels and participants in the course will develop tools suitable to their individual backgrounds. The course is project-based and the course delivery includes seminar presentations from international leading researchers in the field and topic lectures delivered by Professor Selvitella.A team of interested faculty members will serve as co-coaches and guide students in their projects. For more information, feel free to contact Professor Selvitella at aselvite@pfw.edu.
The participating students will be part of the PFW COVID-19 Team and their name will appear under the tab "Team" on the website. Their work on the projects will be showcased at the COVID-19-section of the second edition of the regional conference Data Science Week2020, which will be held at PFW online in December 2020 (here is the link to the first edition).
This course is part of a broader Thematic Program on "DataScience and COVID-19" that Professor Selvitella is organizing at PFW, supported by the Department of Mathematical Sciences and by the College of Arts and Sciences, and whose mission is to learn, teach, and diffuse knowledge about the COVID-19 pandemic.
Should you need assistance registering, contact the Continuing Studies office at learn@pfw.edu.
Who should participate?
This class is of interest to anybody who is interested in data science, mathematics, statistics, and their applications to biology and in particular epidemiology. This class is optimal for people interested in understanding the basic science about infectious diseases, specifically of COVID-19. We welcome anyone who wants to join our initiatives, as we believe the fundamental principle of diversity and inclusion are always crucial, and now more than ever.
Professor Alessandro Maria Selvitella received a BSc and an MSc in Mathematics from Universita' degliStudi di Milano (Milano, Italy), a PhD in Mathematical Analysis from SISSA(Trieste, Italy), and a MSc and a PhD in Statistics from McMaster University(Hamilton, Canada). Alessandro was a Postdoctoral Fellow at McMaster University,and later jointly in the Departments of Computing Science and Psychiatry at University of Alberta. Alessandro joined the Department of Mathematical Sciences at Purdue University Fort Wayne in August 2019, where he is currently Assistant Professor of Data Science and Applied Statistics.
Alessandro's current research interests are in Applied Mathematics, Mathematical Modeling, and in the theory and applications of Machine Learning methods to the Biological and Medical Sciences. For his work, in Spring 2020, he was awarded the Sigma-XiResearcher of the Year Award for the PFW chapter. He is currently the organizer of the "Data Science Week", "Data Science and Machine Learning Seminar Series", and of the 2020/2021 Thematic Program on "Data Science and COVID-19".
