Graduate Student Seminar.

The Grad Seminar is a presentation series arranged by and for graduate students at GW, where students will take turn to deliver talks. These talks may cover a broad spectrum of subjects and are not necessarily limited to one's own research. This seminar seeks to foster a casual environment in which graduate students can acquire skills in delivering technical presentations and get exposed to new challenges in statistics/mathematics. 

The following are the presentation topic/slides of previous speakers (not necessarily from Hu's group).

1. Double-debiased machine learning for treatment and structural parameters (Speaker: Zixuan Zhao, 11.10.2023).

2. High dimensional Classification and clustering with feature selection (Speaker: Yong Wang, 11.17.2023).

3. A benchmark and comparison of active learning for logistic regression (Speaker: Yi Zhang, 12.8.2023).

4. Smoothed quantile regression for analyzing spatial data over complex domains (Speaker: Jilei Lin, 1.26.2024).

5. Causal inference under network interference (Speaker: Zexin Ren, 2.2.2024).

6. Bayesian Iterative Prediction and Lexical-based Interpretation for Disturbed Chinese Sentence Pair Matching (Speaker: Muzhe Guo, 2.16.2024)

7. Subgroup Analyses in clinical trials based on The Desirability of Outcome Ranking (Speaker:Weixiao Dai, 3.1.2024).

8. A review of rerandomization method and comparison (Speaker: Ziji Qin, 3.29.2024).

9. High-dimensional Extreme Quantile Regression (Speaker: Yiwei Tang, 4.12.2024).

10. Gradient Descent Methods on Riemannian Manifolds and Their Applications in Weighted Low Rank Approximation Problem (Conglong Xu, 4.19.2024, GWU Math dept).

11. Deep Learning for partially linear cox model (Speaker: Zixuan Zhao, 8.30.2024).

12. Communication-Efficient Distributed Statistical Inference (Speaker: Jilei Lin, 9.13.2024).

13. Causal inference on distribution functions (Speaker: Zexin Ren, 9.27.2024)

14. Quantile Mediation Analytics (Speaker: Canyi Chen, 10.18.2024, University of Michigan)

15. Explainability in Deep Learning: Concepts, Progress, and Applications (Speaker: Juntao Su, 11.1.2024)

16. Gromov-Wasserstein Optimal Transport: Application-driven Variants, Statistics and Gradient Flow (Speaker: Yaqi Wu, 11.16.2024, GWU Math dept)

17. Predicting individual risk of advanced adenoma based on the interval censored recurrent event and informative screening time (Speaker: Yipeng Wei,12.7.2024)

18. Distributed Inference of Smoothed Quantile Regression for Spatial Data. (Speaker: Jilei Lin, 1.31.2025)

19. Distance Correlation in Multiple Biased Sampling Models (Speaker: Yuwei Ke, 2.7.2025, Queen's University at Kingston)

20. A brief introduction to valid post selection inference (Speaker: Zixuan Zhao, 2.21.2025)

21. Intention-to-diagnose and distinct research foci in diagnostic accuracy studies (Speaker: Yike Wang, 4.16.2025, GWU biostats)

22. Robustness, Heterogeneous Treatment Effects and Covariate Shifts (Speaker: Kieran Zhou, 4.25.2025)

23. Covariate-adjusted response-adaptive designs for time-to-event data (Speaker: Renjie Luo, 9.5.2025)