All talks licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Talk, 15th International Conference of the European Consortium for Informatics and Mathematics Working Group on Computational and Methodological Statistics (CMStatistics), London, UK
I discuss a framework for inference on general model-agnostic variable importance measures and possible summary measures for longitudinal variable importance.
Talk, Forum on the Integration of Observational and Randomized Data, Washington, DC
I discuss a framework for predicting safety outcomes of interest within the FDA’s Sentinel system using data from electronic health records.
Talk, International Chinese Statistical Association Applied Statistics Symposium, Gainesville, FL
I discuss a framework for inference on general model-agnostic variable importance measures and possible summary measures for longitudinal variable importance.
Talk, WNAR 2022, Virtual
I discuss a method for model-agnostic variable selection that is robust to model misspecification and valid in settings with missing data.
Talk, University of Washington Department of Biostatistics Seminar Series, Virtual
I discuss a framework for inference on general model-agnostic variable importance measures, and how this framework can be used to perform variable selection. I also briefly discuss several directions of current work, including longitudinal variable importance; a measure of how important variables are for tailoring treatment; and fairness-aware variable importance.
Talk, American Statistical Association Statistical Learning and Data Science Webinar Series, Virtual
I discuss a framework for inference on general model-agnostic variable importance measures.
Talk, Joint Statistical Meetings, Virtual
I gave a talk on work in progress, developing methods for variable selection in settings with missing data that do not rely on (generalized) linear models.
Talk, 3rd Annual Hutch United Symposium, Virtual
Keynote talk at the 3rd annual Hutch United Symposium.
Talk, Kaiser Permanente Washington Health Research Institute Seminar Series, Virtual
I discuss a framework for inference on general model-agnostic variable importance measures.
Talk, Fred Hutchinson Cancer Research Center Biostatistics Program Seminar Series, Virtual
I discuss three approaches towards a more principled use of machine learning: inference on the goodness of fit, inference on variable importance, and containerization.
Talk, Roanoke Valley Governor's School Computational Biology Course, Virtual
Guest lecture on some of the ways that statistics is used in infectious disease research in the Computational Biology course at Roanoke Valley Governor’s School.
Talk, Vanderbilt University Department of Biostatistics Seminar, Virtual
I discuss a framework for inference on general model-agnostic variable importance measures.
Talk, 37th International Conference on Machine Learning, Virtual
We discuss our paper to be published in the Proceedings of the Thirty-seventh International Conference on Machine Learning.
Talk, 27th International Dynamics and Evolution of HIV and Other Human Viruses Meeting, Virtual
Contributed talk at the 27th International Dynamics and Evolution of HIV and Other Human Viruses Meeting on SLAPNAP (see publications).
Talk, Joint Statistical Meetings, Denver, CO
This talk (on a preliminary version of my general variable importance paper published in Journal of the American Statistical Association) was selected for an ASA Nonparametrics Section Travel Award.
Talk, UW Biostatistics Colloquium, Seattle, WA
Invited talk on my dissertation research given at the UW Biostatistics Colloquium.
Talk, Joint Statistical Meetings, Baltimore, MD
This talk (on a preliminary version of my R-squared variable importance paper published in Biometrics) was selected for an ASA Biometrics Section Travel Award.
Talk, Thirty-fifth International Conference on Machine Learning, Virtual
Contributed talk at the Thirty-fifth International Conference on Machine Learning.
Talk, WNAR of the International Biometric Society, Santa Fe, NM
This talk (on a preliminary version of my R-squared variable importance paper published in Biometrics) was selected as the Most Outstanding Oral Paper.