Talks

2023

Sensitivity analysis via stochastic programming

2023-12-20 1:10 PM — 1:30 PM Lisbon, Portugal
Slides

Confounder selection via iterative graph expansion

2023-09-17 12:00 AM — 12:00 AM Peking University, China
Slides Video

Using Mendelian randomization to discover biological mechanisms

2023-08-10 — Toronto, Canada
Project Slides

Almost exact Mendelian randomization

By combining causal graphs and randomization inference, a formal justification for Mendelian randomization is given in the context of with-family studies.
2023-04-20 10:00 AM — 10:20 AM Oslo, Norway
Project Project Slides

Simultaneous hypothesis testing using negative controls

Negative control is a common technique in scientific investigations and broadly refers to the situation where a null effect (“negative …
2023-03-29 12:00 PM — 1:00 PM University of Pennsylvania
Slides

2022

The randomization principle in causal inference: A modern look at some old ideas

Randomization is a fundamental principle in causal inference and was first proposed by R A Fisher about a century ago. Although …
2022-12-02 2:00 PM — 3:00 PM Imperial College, London
Project Project Slides

A crash course on causal inference

2022-09-07 1:00 PM — 2:00 PM CCAIM Summer School
Slides

Multiple conditional randomization tests

2022-08-31 1:45 PM — 2:15 PM Bremen, Germany
Project Slides

Multiple conditional randomization tests

2022-06-27 5:10 PM — 5:30 PM London
Project Slides

Two High-Profile Examples of Selection Bias

This talk will examine the selection bias that occurred in studying some most contentious problems. In the first case study, we will …
2022-05-11 12:30 PM — 1:30 PM Center for Statistics and the Social Sciences, University of Washington
Project Slides

Fisher, Statistics, and Randomization

One of Fisher’s most important scientific contributions is the paradigm of randomized experiments. I will try to trace the origin of …
2022-04-22 9:00 AM — 10:00 AM Gonville & Caius College, Cambridge
Project Slides

How infectious was COVID-19 when it first circulated in Wuhan?

This is given to A-level students.
2022-03-24 2:00 PM — 2:45 PM Corpus Christi College Masterclass in Mathematics
Project Slides

What is a randomization test?

2022-03-23 2:00 PM — 3:00 PM University of Toronto
Project Slides

2021

Leverage Mendelian Randomization to Learn Meaningful Representations (LMR×2)

2021-12-14 5:30 PM — 6:00 PM LMRL NeurIPS workshop
Project Slides

Multiple conditional randomization tests

2021-09-29 9:30 PM — 10:30 PM UC Berkeley Causal Inference Group
Project Slides

Small Data, Big Time—A retrospect of the first weeks of COVID-19

2021-09-08 5:15 PM — 7:15 PM Manchester, UK
Project Slides Video

Reliable Inference for Precision Medicine

Two central objectives of individualized treatment are precision and optimality. A third objective is robustness, and this talk aims to …
2021-08-09 2:00 PM — 2:25 PM JSM 2021 (Online)
Authors. --
Slides

BETS: The dangers of selection bias in early analyses of the coronavirus disease (COVID-19) pandemic

The coronavirus disease 2019 (COVID-19) has quickly grown from a regional outbreak in Wuhan, China to a global pandemic. Early …
2021-06-15 12:00 PM — 1:00 PM Ghent University
Slides

Mendelian randomization: Old and new insights

Mendelian randomization (MR) is a method for causal inference that utilizes the natural experiment in genetic inheritance. The idea of …
2021-04-16 6:00 PM — 7:00 PM University of Pennsylvania
Project Slides

Mendelian randomization: Old and new insights

Mendelian randomization (MR) is a method for causal inference that utilizes the natural experiment in genetic inheritance. The idea of …
2021-03-26 3:00 PM — 4:00 PM EPFL
Project Slides

BETS: The dangers of selection bias in early analyses of the coronavirus disease (COVID-19) pandemic

2021-03-24 4:00 PM — 5:00 PM Infectious disease outbreaks webinar
Slides

Discussion on 'Causal Inference in Genetic Trio Studies'

Discussion on Dr Stephen Bates’ talk in the Online Causal Inference Seminar.
2021-01-26 Online Causal Inference Seminar (Zoom meeting)
Slides Video

Selecting and ranking individualized treatment rules with unmeasured confounding

2021-01-14 4:30 PM — 5:30 PM Selective Inference Webinar
Slides

2020

Selection bias in 2020

This talk will examine the selection bias that occurred in studying some most contentious problems in 2020. In the first case study, we …
2020-12-08 Online Causal Inference Seminar (Zoom meeting)
Project Slides Video

Discovering mechanistic heterogeneity using Mendelian randomization

Mendelian Randomization (MR) is a popular method in epidemiology and genetics that uses genetic variation as instrumental variables for …
2020-09-26 Peking University (Online Zoom meeting)
Code Project Slides

BETS: The dangers of selection bias in early analyses of the coronavirus disease (COVID-19) pandemic

2020-09-24 Department of Statistics, Ohio State University
Slides

Sensitivity analysis for observational studies

Sensitivity analysis is widely recognized as a critical step in an observational study but is seldom found in applications. One reason …
2020-09-08 5:00 PM — 6:00 PM Department of Biostatistics, Yale University
Slides Video

Using sparsity to overcome unmeasured confounding

Sparsity is often used to improve the interpretability of a statistical analysis and/or reduce the variance of a statistical estimator. …
2020-08-25 11:10 AM — 12:40 PM ISCB 2020 (Virtual)
Slides

Bootstrapping sensitivity analysis

2020-08-03 JSM 2020 (Virtual)
Slides

BETS: The dangers of selection bias in early analyses of the coronavirus disease (COVID-19) pandemic

2020-05-05 Department of Biostatistics, Yale University
Slides Video

Causal inference: An introduction

Introduction to causal inference for social science PhD students.
2020-03-04 2:00 PM — 4:00 PM University of Cambridge
Slides

The cycle of statistical research

More than fifty years ago, John Tukey first envisioned a field we now call “Data Science” (he called it “Data …
2020-02-19 3:00 PM — 4:00 PM MR14, Centre for Mathematical Sciences, Cambridge
Slides

2019

Using sparsity to overcome unmeasured confounding: Two examples

Sparsity is often used to improve the interpretability of a statistical analysis and/or reduce the variance of a statistical estimator. …
2019-10-15 2:00 PM — 3:00 PM MRC Biostatistics Unit, University of Cambridge
Slides

MR Data Challenge 2019

This report entered the 2019 MR Data Challenge and contains reproducible R code for our analysis.
2019-07-19 MRC Integrative Epidemiology Unit, University of Bristol
Project Slides

The statistics of summary-data Mendelian randomization

Invited talk giving an overview of my research on summary-data Mendelian randomization.
2019-07-17 MRC Integrative Epidemiology Unit, University of Bristol
Project Slides

Mendelian randomization: A tutorial

Tutorial talk for the theory, methods, and practice of Mendelian randomization.
2019-07-12 Rutgers University, School of Public Health
Project Slides