Entry in Mathematics Genealogy

Current Group Members:

• Alex Chen (Ph.D. student).
• Stella Huang (Ph.D. student).
• Yijia Zhao (Ph.D. student).

Former Group Members:

Ph.D. Students

• Stephen Smith (2023). Local causal structure learning with the coordinated multi-neighborhood learning algorithm.
• Hao Wang (2022). Constraint-based learning of interventional Markov equivalence classes on high-dimensional data.
• Gabriel Ruiz (2022). Plug-in estimation approaches to causal inference and discovery.
• Dale Kim (2022). Learning factor analysis structures: A clique search method on correlation thresholded graphs and a piecewise linear spline approach.
• Jireh Huang (2022). Directed acyclic graph: Partitioned hybrid structure learning and Bayesian causal bandits.
• Hangjian Li (2021). Structure learning of Gaussian DAGs from network data.
• Zhanhao Peng (2021). Graphon estimation by empirical Bayes approach and causal discovery from multiple populations.
• Qiaoling Ye (2021). Order-based learning of Bayesian networks: regularized Cholesky score and distributed data.
• Bingling Wang (2020). Structure learning of DAGs from observational data with multivariate spatial processes and with non-invertible functional relationships.
• Kun Zhou (2020). Joint and post-selection confidence sets for high-dimensional regression.
• Seunghyun Min (2019). High-dimensional inferences via estimator augmentation: post-selection and group structure.
• Jiaying Gu (2018). Structure learning of Bayesian networks: group regularization and divide-and-conquer.
• Bryon Aragam (2015). Structure learning of linear Bayesian networks in high-dimensions.
• Maria Cha (2015). Detecting combinatorial DNA-binding patterns by the K-function and its generalizations.
• Yuliya Marchetti (2014). Solution path clustering with minimax concave penalty and its applications to noisy big data.
• Matthew Levinson (2013). Penalized Bayesian model selection and prediction for gene regulation in higher organisms.
• Fei Fu (2012). Sparse causal network estimation with experimental intervention.
• Gong Chen (2010). Modeling and analysis of multiple alignments, ChIP-seq data, and gene expression data for finding transcription factor binding sites.
• Michael Mason (2010). Machine learning approaches to understanding gene regulation in mouse embryonic stem cells.

Master's Students

• Steven Turnbull (2024), Raymond Benitez (2024), James Tang (2024), Minxuan Xu (2018), Jordan Berninger (2018, co-chair), Ruifu Jiang (2018), Jixuan Li (2018), Xiaolu Yu (2017), Fan Zhang (2017), Dacheng Zhang (2016), Megan Kuhfeld (2016), Marika Csapo (2015), Jia He (2015), Jinchao Li (2015), Wenjia Wang (2014), Yuju Lee (2014), Jun Liu (2013), Albert Wong (2013), Ye Gao (2011), Jung In Kim (2010), Haiqiang Wang (2009), Jin Wook Lee (2009).

Rotation Students

• Joshua Lim (Statistics, 2023-2024), Zijun Zhang (Bioinformatics, 2015), Chengyang Wang (Bioinformatics, 2015), Wei Tang (Physics, 2011-2012), Pengcheng Li (Bioinformatics, 2010-2011).