Qingyuan Zhao

Name:	Qingyuan Zhao
Affiliation:	Statistical Laboratory
E-mail:	(only provided to users who are logged into talks.cam)
Last login:	9 Mar 2026, 9:09 a.m.

Public lists managed by Qingyuan Zhao

• Causal Inference Reading Group
• Peter Whittle Lecture
• Statistics

Talks given by Qingyuan Zhao

Obviously this only lists talks that are listed through talks.cam. Furthermore, this facility only works if the speaker's e-mail was specified in a talk. Most talks have not done this.

• On statistical models associated with acyclic directed mixed graphs
• A matrix algebra for graphical statistical models
• [Journal Club] Granger Causality: A Review and Recent Advances
• Journal Club: Separable Effects for Competing Events
• Identification In Missing Data Models Represented By Directed Acyclic Graphs
• Dynamic Treatment Regimes III
• The Cycle of Statistical Research
• Dynamic treatment regimes II
• Dynamic treatment regimes I
• Anchor regression
• The Blessing of Multiple Causes
• High dimensional data and latent confounding I

Talks organised by Qingyuan Zhao

This list is based on what was entered into the 'organiser' field in a talk. It may not mean that Qingyuan Zhao actually organised the talk, they may have been responsible only for entering the talk into the talks.cam system.

• Kernel Ridge Regression Inference with Applications to Preference Data
• Local causal discovery for downstream effect estimation
• Leveraging multi-study, multi-outcome data to improve external validity and efficiency of clinical trials for managing schizophrenia
• Leveraging multi-study, multi-outcome data to improve external validity and efficiency of clinical trials for managing schizophrenia
• Genetics-based drug discovery: Some stories from the frontline
• Assumption-lean Inference for Generalised Linear Model Parameters
• [Journal Club] Granger Causality: A Review and Recent Advances
• Response-adaptive randomization in clinical trials: from myths to practical considerations
• Bayesian Inference using Generative Models
• Biostatistics: successes, challenges and opportunities
• Simulation of random fields on Riemannian manifolds
• Flexible Multiple Testing with All-Resolutions Inference
• Local Independence Graphs
• Latent space models for multiplex networks with shared structure
• Root and community inference on Markovian models of networks
• Comparison of Markov chains via weak Poincaré inequalities, with application to pseudo-marginal MCMC
• Long Story Short: Omitted Variable Bias in Causal Machine Learning
• Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data
• Counterfactual inference in sequential experimental design
• (CANCELLED) Stochastic Causal Programming for Bounding Treatment Effects
• Unbiased Set-Estimation of Heterogeneous Causal Effects
• A machine learning approach for causal structure estimation in high dimensions
• Optimal prediction of Markov chains without mixing conditions
• Optimal prediction of Markov chains without mixing conditions
• Minimum L1-norm interpolators: Precise asymptotics and multiple descent
• Minimum L1-norm interpolators: Precise asymptotics and multiple descent
• Systematic inducement of sparsity
• Random Planted Forest: a directly interpretable tree ensemble
• Interpretable Model-Independent Detection of New Physics Signals
• TBC
• TBC
• Robust inference for intractable likelihood models using kernel divergences
• Two-sample testing of high-dimensional linear regression coefficients via complementary sketching
• Two-sample testing of high-dimensional linear regression coefficients via complementary sketching
• CANCELLED: Systematic inducement of sparsity
• Variable elimination and graph reduction: towards an efficient g-formula for causal DAGs
• Random Graph Asymptotics for Treatment Effect Estimation under Network Interference
• New Approaches for Inference on Optimal Treatment Regimes
• MARS via LASSO
• Kernel Thinning and Stein Thinning
• TBC
• Global testing for dependent Bernoullis
• Causal Inference for Nonlinear Outcome Models with Possibly Invalid Instrumental Variables
• Sharp Sensitivity Analysis for Inverse Propensity Weighting via Quantile Balancing
• Fair Data Adaptation with Quantile Preservation
• Structural Nested Models and G-estimation: The Partially Realized Promise
• A Negative Correlation Strategy for Bracketing in Difference-in-Differences
• Synthetic Difference in Differences
• Minimax Crossover Designs
• A Formal Causal Interpretation of the Case-Crossover Design
• Bias and high-dimensional adjustment in observational studies of peer effects
• Partial identification in instrumental variables
• Identification In Missing Data Models Represented By Directed Acyclic Graphs
• Causal Inference in Genetic Trio Studies
• Dynamic Treatment Regimes III
• Title to be confirmed
• Stable prediction
• Dynamic treatment regimes II
• Graphical models for extremes
• Dynamic treatment regimes I
• Negative controls in causal inference
• Regression discontinuity design
• Anchor regression
• Higher-order influence function
• Tackling invalid instrumental variables
• The Blessing of Multiple Causes
• High dimensional data and latent confounding II
• High dimensional data and latent confounding I