Selective Randomization Inference for Adaptive Experiments
Bernoulli-IMS 11th World Congress in Probability and Statistics - Bochum, Germany
Tobias Freidling
PhD student in Statistics
About Me
I am a PhD student at the University of Cambridge supervised by Qingyuan Zhao. My current research focuses on causal inference, sensitivity analysis and randomization inference.
Beyond this, I undertook industry projects in the implementation of RNNs with Tensorflow, Bayesian optimal experimental design and detection of synthetically lethal gene pairs based on CRISPR knock-out experiments. I am also a consultant at Cambridge’s Statistics Clinic.
In 2025, I will join Mats Stensrud’s group at EPFL as a postdoctoral researcher.
Interests
- Causality
- Sensitivity Analysis
- Randomization Inference
- Stochastic Optimization
- Selective Inference
- Applied Statistics
Education
M.Sc. Mathematics, 2020
Technical University of Munich
Exchange Research Student, 2020
Kyoto University
Visiting Student, 2018
University of Oxford
B.Sc. Mathematics, 2017
Ludwig Maximilian University, Munich
Publications and Pre-Prints
(2024).
Optimization-based Sensitivity Analysis for Unmeasured Confounding using Partial Correlations.
(2021).
Post-selection Inference with HSIC-Lasso.
ICML 2021.
(2021).
Confidence in Causal Discovery with Linear Causal Models.
UAI 2021.
(2020).
Model Uncertainty in Statistical Inference.
Master Thesis.
Featured Talks
Selective Randomization Inference for Adaptive Studies
American Causal Inference Conference - Seattle, WA, USA
Sensitivity Analysis with the R2-Calculus
European Causal Inference Meeting - Oslo, Norway
Sensitivity Analysis with the R2-Calculus
Online Causal Inference Seminar - online
Post-selection inference with HSIC-Lasso
International Conference on Machine Learning - online
Teaching at the University of Cambridge
- Teaching Assistant
- Causal Inference (Part III): 2021, 2022
- Supervisor
- Statistical Modelling (Part II): 2023
- Statistics (Part IB): 2023
- Mathematics of Machine Learning (Part II): 2022