2022-06-10
Associations’ News
The main objective of the Data Science Year at the UDP is to engage and to involve students, researchers, and practitioners in the data science arena by creating a space to learn and discuss multiple topics associated with this discipline and its applications. We have organized two new virtual seminars with prestigious exponents of the area. We invite you to join us!
Seminar: Statistical and Machine Learning Approaches to Solar Flare Forecasting
Speaker: Prof. Yang Chen, University of Michigan, Ann Arbor, USA
Date: Wednesday, 29 June 2022, 11:30 am Chilean time
Registrations here.
Abstract
“Solar flare prediction is an important task, which impacts national power grid robustness, satellite signal stability, and safety of astronauts’ exploration of space. In recent years, the solar flare prediction problem has caught more attention among the machine learning and statistics community. In this talk, I will give an introduction on our efforts on solar flare forecasting with existing and innovative machine learning and statistical models. We obtain highly competitive results for flare forecasting with highly interpretable models, which contributes both to operational use and the science itself.” – Prof. Yang Chen.
Yang Chen received her Ph.D. (2017) in Statistics from Harvard University and joined the University of Michigan as an Assistant Professor of Statistics and Research Assistant Professor at the Michigan Institute of Data Science (MIDAS). She received her B.A. in Mathematics and Applied Mathematics from the University of Science and Technology of China. Research interests include computational algorithms in statistical inference and applied statistics in the field of biology and astronomy.
Seminar: Signal and Noise - Hotspots Jump Out of the Norm
Speaker: Eunice Kim, Data Scientist at Microsoft, USA
Date: Wednesday, 13 July 2022, 11.30 am Chilean time
Registrations here.
Abstract
“Humans easily detect something that is out of the ordinary. That presupposes that we establish a norm, have some measurements and/or a detectable (visual, aural, or olfactory) aid to understand what we experience and observe. How do statistics and data science come into play when there is a need to detect anomalies and provide a response to the anomalies? What are the conditions given? How do we set up the problem when we have little knowledge of the domain? I draw examples from my work and share what I have found to be necessary for analysis and collaboration.” – Eunice Kim.
Eunice Kim is a data scientist at Microsoft. She has a passion for teaching and solving complex problems with an investigative, statistical lens. Previously, she taught undergraduate students in engineering at Iowa State University and liberal arts majors at Amherst College. Besides teaching introductory statistics courses and research methods, she recalls the challenge and joy of introducing spatial statistics to undergraduates. Her research application is in the environmental and economic context where she brings her specialty in spatial statistics to draw out patterns. She has a Bachelor’s Degree in Mathematics and Economics, and Master’s and PhD in Statistics. She volunteers on the new client acquisition team of Statistics Without Borders and serves as chair of the Committee on Women in Statistics of the American Statistical Association.
Please mark your calendars and extend this invitation to all students. The seminars will be held virtually using the platform Zoom. Further information here.
Local Organizing Committee: Alba Martinez-Ruiz, Paula Fariña, Raúl Pezoa-Zamorano, Francisco Jara-Moroni.
Supporting institutions: International Association for Statistical Computing, International Statistical Institute, and Chilean Statistical Society.