Conference programme

View the full programme for the in-person conference in Manchester.

Register for on-demand access (available until 8 October).

Both included the following keynote speakers:

Melinda Mills MBE, FBA is director of the Leverhulme Centre for Demographic Science at the University of Oxford. 

Eric Tchetgen Tchetgen is the Luddy Family President’s Distinguished Professor and Professor of Statistics from the Wharton School, University of Pennsylvania.

Bin Yu is the chancellor's distinguished professor in the Departments of Statistics and of Electrical Engineering & Computer Sciences at the University of California at Berkeley. She delivered this year’s Campion (President’s Invited) Lecture

Jonty Rougier, who won this year's Barnett Award, delivered the Barnett lecture focusing around his award-winning work in environmental sciences. 

Tom Chivers is the science editor at UnHerd and David Chivers is professor of economics at Durham University. Together, they delivered this year's Significance lecture on their recent book, How To Read Numbers.

See below the speakers for our Discussion Meeting at Conference on the 8th of September:

Paper 1: 'Modeling the COVID-19 infection trajectory:  a piecewise linear quantile regression approach'

Feiyu Jiang
Feiyu Jiang is currently an Assistant Professor in Department of Statistics at Fudan University. He received his Ph.D. in statistics from Tsinghua University this summer. His research interests include nonlinear time series analysis,  change-point analysis and financial econometrics.

Shao Xiaofeng
Xiaofeng Shao received his PhD in Statistics from the University of Chicago in 2006 and has since been a faculty member with the Department of Statistics at the University of Illinois Urbana-Champaign. His current research interests include time series analysis, change-point analysis, functional data analysis, high dimensional data analysis and their applications. He is a fellow of Institute of Mathematical Statistics (IMS) and American Statistical Association (ASA).

Zifeng Zhao
Zifeng Zhao received his PhD in Statistics from the University of Wisconsin-Madison in 2018 and is currently an Assistant Professor in the Department of Information Technology, Analytics, and Operations at the University of Notre Dame. His current research interests include change-point analysis, time series analysis, functional data analysis, copula modeling, and their applications.

Paper 2: 'Quantifying the economic response to COVID-19 mitigations and death rates via forecasting Purchasing Managers' Indices using Generalised Network Autoregressive models with exogenous variables'

Guy Nason

Guy Nason is Chair in Statistics at Imperial College London and currently a co-Director of I-X, a major new cross-faculty initiative focusing on research, education and entrepreneurship in `Human and Machine Learning' at Imperial’s White City Campus. His research interests are currently in time series, superoscillation, machine learning, official statistics and statistical governance.

James Wei

James Wei is a PhD candidate in the Modern Statistics and Statistical Machine Learning ESPRC Center for Doctoral Training at Imperial College London, where he focuses on developing machine learning methods for time series forecasting and nonparametric regression. Before starting his PhD, James spent five years working as a quantitative researcher in the finance sector. He graduated with an MSc in Statistics in 2019 and a BSc in Economics in 2014, both at the London School of Economics. 

Paper 3: 'Small Data, Big Time---A retrospect of the first weeks of COVID-19'

Qingyuan Zhao

Qingyuan Zhao was born and raised in Wuhan, China and is currently a University Lecturer in the Statistical Laboratory at the University of Cambridge. He obtained his PhD in Statistics from Stanford University in 2016 and spent three years at the University of Pennsylvania as a postdoctoral fellow before joining Cambridge in 2019. His research interests include causal inference and applied statistics.