SSA NSW October Meeting - Christopher K Wikle - 2024 Data Science and Statistics (DSS) Lecture, from School of Mathematics and Applied Statistics, University of Wollongong (UOW)

The SSA NSW branch is thrilled to collaborate with UOW School of Mathematics and Applied Statistics on their annual Data Science and Statistics (DSS) Lecture. This year's lecturer is Christopher K Wikle, Distinguished Professor in the Department of Statistics at the University of Missouri, USA.

Date: Wednesday 30 October 2024

Time: 11.30am - 12.30pm: in-person-only lecture, with light refreshments to follow

Venue: Building 43 Room G01, University of Wollongong, parking available on campus for carpool. Sign up here to carpool. 

RSVP: Register here.

Speaker: Christopher K Wikle

Title:  The Ship Has Sailed: Where Should We Steer It? (Climate Adaptation Needs Uncertainty Quantification)

Abstract:

Earth’s climate is changing due to anthropogenic influences. Although there are still well-meaning attempts to mitigate the drivers of this change (e.g., reduction of greenhouse gas emissions), it is widely believed that such changes will be “too little, too late.” Thus, for many, the focus has shifted to “climate change adaptation” in which decision makers modify their response to or anticipation of the numerous risks associated with climate change. There are many different approaches that can be taken when one adapts to climate change, ranging from resistance to retreat. The decision on the most appropriate way forward (how to steer the ship) requires a coherent, cohesive, and collective response across localities, sectors of society, and scales of governance. Such decisions require information from many different sources (e.g., from climate models, from impact assessments, from political and social scientists, …), and these sources come with uncertainty. In addition, this process is inherently multi-disciplinary and requires teams of scientists and decision makers working together. Although it is well known that informed decisions must account for uncertainty, quantification of that uncertainty across multiple disciplines, information sources, and complex decision pathways is in its infancy. This relatively non-technical talk will describe some of the challenges and will argue that statistical science offers a path forward through multi-level (deep) modelling. Such approaches will likely borrow from Bayesian statistics as well as utilise modern surrogate modelling techniques and hybrid “AI”-statistical methods. Several examples will be presented to illustrate these points. 

Biography:

Christopher K. Wikle is Curators’ Distinguished Professor and Chair of Statistics at the University of Missouri (MU), with additional appointments in Soil, Environmental and Atmospheric Sciences and the Truman School of Public Affairs. He received a PhD co-major in Statistics and Atmospheric Science in 1996 from Iowa State University. He was research fellow at the National Center for Atmospheric Research from 1996-1998, after which he joined the MU Department of Statistics.

His research interests are in spatial and spatio-temporal statistics applied to environmental, ecological, geophysical, agricultural and federal survey applications, with particular interest in dynamics. His work has been concerned with formulating computationally efficient deep hierarchical Bayesian models motivated by scientific principles, with more recent work at the interface of deep neural models in machine learning.

Awards include elected Fellow of the American Statistical Association (ASA), Institute of Mathematical Statistics (IMS), elected Fellow of the International Statistical Institute (ISI), Distinguished Alumni Award from the College of Liberal Arts and Sciences at Iowa State University, ASA Environmental (ENVR) Section Distinguished Achievement Award, co-awardee 2017 ASA Statistical Partnership Among Academe, Industry, and Government (SPAIG) Award, the MU Chancellor’s Award for Outstanding Research and Creative Activity in the Physical and Mathematical Sciences, the Outstanding Graduate Faculty Award, and Outstanding Undergraduate Research Mentor Award. His book Statistics for Spatio-Temporal Data (co-authored with Noel Cressie) was the 2011 PROSE Award winner for excellence in the Mathematics Category by the Association of American Publishers and the 2013 DeGroot Prize winner from the International Society for Bayesian Analysis. His latest book, Spatio-Temporal Statistics with R, with Andrew Zammit-Mangion and Noel Cressie, was published in 2019 and won the 2019 Taylor and Francis award for Outstanding Reference/Monograph in the Science and Medicine category. Dr. Wikle is Associate Editor for several journals and is one of six inaugural members of the Statistics Board of Reviewing Editors for Science.