Keynote Speakers

Keynote: Sophia Rabe-Hesketh
We are excited to announce that Professor Sophia Rabe-Hesketh will present the MSSISS 2020 keynote address. Sophia Rabe-Hesketh is a Professor of Educational Statistics and Biostatistics at the University of California, Berkeley. She was previously Professor of Social Statistics at the Institute of Education, University of London and Reader in Statistics at the Institute of Psychiatry, University of London.

Date: February 28, Friday

Location: Michigan League

Title: Handling Missing Data by Creating More Missing Data

Abstract:

To be coming

Bio:

Sophia Rabe-Hesketh is a statistician whose research interests include multilevel/hierarchical modeling, item response theory, longitudinal data analysis, and missing data. She has over 100 peer-reviewed articles in over 60 different journals including PsychometrikaJournal of EconometricsBiometricsJournal of the Royal Statistical Society, Series A, with an h-index of 58 in Google Scholar. She has developed a modeling framework for a wide range of multilevel and latent variable models called GLLAMM (Generalized Linear Latent and Mixed Modeling) and written a publicly available software package called gllamm (http://www.gllamm.org/(link is external)) to estimate these models. The theory of these models is published in Generalized Latent Variable Modeling(link is external), co-authored with Anders Skrondal. Since 2002, her gllamm software has been used in over 1000 peer-reviewed papers in over 700 different journals by researchers in education, sociology, political science, economics, medicine, and statistics.

Sophia Rabe-Hesketh was elected to the National Academy of Education in 2015 and was President of the Psychometric Society in 2014-2015. She is a member of the Design and Analysis Committee for the National Assessment of Educational Progress (NAEP) and of the Techincal Advisory Group for the Program for International Student Assessment (PISA). She has been Associate Editor for Psychometrika among others and served on Editorial Boards for Journal of Educational and Behavioral StatisticsPsychological Methods, and others.

Sophia Rabe-Hesketh is also a member of the Interdepartmental Group in Biostatistics(link is external) at the University of California, Berkeley. She was previously Professor of Social Statistics at the Institute of Education, University of London.

Michigan Junior Faculty Keynote: Yang Chen
Yang Chen
We are excited to welcome Assistant Professor Yang Chen as the MSSISS 2020 Thursday evening junior faculty speaker.

Date: February 27, Thursday

Location: Michigan League

Title: Solar Flare Prediction with Machine Learning Methods

Abstract:

Over the space age, we have accumulated extensive knowledge of the regions of space surrounding the Earth and the Sun, and the governing physical processes controlling space weather in these regions. However, this knowledge has not been translated into an operational forecast capability. By combining expertise in space weather modeling and data science, we can address the” holy grail” of space weather prediction: extending the forecast horizon from minutes to days. In this talk, I present our machine learning efforts, which show great promise towards early predictions of solar flare events. We build a data pre-processing pipeline that is built to extract useful data from multiple sources — Geostationary Operational Environmental Satellites (GOES) and Solar Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager (HMI) and SDO/Atmospheric Imaging Assembly (AIA) — to prepare inputs for machine learning algorithms. For our strong/weak flare classification model, case studies show a significant increase in the prediction score around 20 hours before strong solar flare events, which implies that early precursors appear at least 20 hours prior to the peak of a flare event. Ongoing and future work will be discussed in the talk.

Bio:

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.