Lili Zheng

I am a postdoctoral researcher in the Department of Electrical and Computer Engineering at Rice University, advised by Prof. Genevera Allen. Previously, I completed my Ph.D. in the Department of Statistics at the University of Wisconsin-Madison, under the supervision of Prof. Garvesh Raskutti. I received my bachelor's degree at the University of Science and Technology of China (USTC) in 2016. Research interest: I am broadly interested in developing efficient and trustworthy statistical methods for large-scale and complex real-world data set. In particular, I have been working on the following topics: graphical models, Granger causality networks, missing data, model-agnostic variable importance, high-dimensional inference, tensor data analysis, stochastic algorithms, non-convex optimization. I will join UIUC Statistics as an Assistant Professor in Fall 2024! E-mail: lz67 [AT] rice [DOT] edu Google Scholar CV

Working Papers

(*: equal contribution)

• Cluster Quilting: Spectral Clustering for Patchwork Learning
  Lili Zheng, Andersen Chang, Genevera I. Allen
  

Preprints

(*: equal contribution)

• Joint Semi-Symmetric Tensor PCA for Integrating Multi-modal Populations of Networks
  Jiaming Liu*, Lili Zheng*, Zhengwu Zhang, Genevera I. Allen
  Submitted

• High-dimensional Multi-class Classification with Presence-only Data
  Lili Zheng, Garvesh Raskutti
  Under revision at Electronic Journal of Statistics

• Model-Agnostic Confidence Intervals for Feature Importance: A Fast and Powerful Approach Using Minipatch Ensembles
  Luqin Gan*, Lili Zheng*, Genevera I. Allen
  

• Low-Rank Covariance Completion for Graph Quilting with Applications to Functional Connectivity
  Andersen Chang, Lili Zheng, Genevera I. Allen
  Under revision at Journal of the American Statistical Association, Applications and Case Studies

Publications

(*: equal contribution)

• Interpretable Machine Learning for Discovery: Statistical Challenges & Opportunities
  Genevera I. Allen, Luqin Gan, Lili Zheng
  Annual Review of Statistics and Its Application. 2023

• Nonparanormal Graph Quilting with Applications to Calcium Imaging
  Andersen Chang*, Lili Zheng*, Gautam Dasarathy, Genevera I. Allen
  STAT. 2023

• Graphical Model Inference with Erosely Measured Data
  Lili Zheng, Genevera I. Allen
  Journal of the American Statistical Association, Theory and Methods. 2023 [Code]

• Gaussian Process Parameter Estimation Using Mini-batch Stochastic Gradient Descent: Convergence Guarantees and Empirical Benefits
  Hao Chen*, Lili Zheng*, Raed Al Kontar, Garvesh Raskutti (*: equal contribution)
  Journal of Machine Learning Research. 2022

• Optimal High-order Tensor SVD via Tensor-Train Orthogonal Iteration
  Yuchen Zhou, Anru R. Zhang, Lili Zheng, Yazhen Wang
  IEEE Transactions on Information Theory. 2022 [Code]
  

• Context-dependent Self-exciting Point Processes: Models, Methods, and Risk Bounds in High Dimensions
  Lili Zheng, Garvesh Raskutti, Rebecca Willett, Benjamin Mark
  Journal of Machine Learning Research. 2021 [Slides][Code]
  

• Testing for High-dimensional Network Parameters in Auto-regressive Models
  Lili Zheng, Garvesh Raskutti
  Electronic Journal of Statistics. 2019 [Code]
  

• A Low-Rank Tensor Completion Approach for Imputing Functional Neuronal Data from Multiple Recordings
  Lili Zheng, Zachary T. Rewolinski, Genevera I. Allen
  IEEE Data Science and Learning Workshop (DSLW). 2022

• Learning Gaussian Graphical Models with Differing Pairwise Sample Sizes
  Lili Zheng, Genevera I. Allen
  International Conference on Acoustics, Speech, and Signal Processing (ICASSP). 2022

• Stochastic Gradient Descent in Correlated Settings: A Study on Gaussian Processes
  Hao Chen*, Lili Zheng*, Raed Al Kontar, Garvesh Raskutti
  Neural Information Processing Systems (NeurIPS). 2020 [Video][Code]