Yang Ni(倪羊)

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Department of Statistics and Data Sciences
The University of Texas at Austin

Greetings! My name is Yang Ni (/y-ah-ng nee/). I'm currently (Jan 2016 - now) a post-doc fellow at UT Austin working with Dr. Peter MüllerBefore I joined UT, I spent 3.5 years (Aug 2012 - Dec 2015) in Rice University to get my PhD degree in statisticssupervised by Dr. Francesco Stingo and Dr. Veera Baladandayuthapani from MD Anderson Cancer Center. 

Areas of Interest

Methodology: Graphical models, Bayesian nonparametrics, big data computation, variable selection, clustering and feature allocation, classification.
Application: Gene/protein networks reconstruction, integrative genomics, clinical trial design, tumor heterogeneity, precision medicine, biomarker detection, genetics, neuroscience, electronic health records and tax fraud detection.

Paper In Preparation

[9] "Bayesian Nonparametric Two-sample Test for Equality of High-dimensional Means."
[8] "Joint Analysis of Time-to-event and Longitudinal Data with Application to Chronic Kidney Disease Detection in Electronic Medical Records Data."
[7] "Double-feature Allocation Models for Disease Mining in Electronic Health Records Data."
[6] "GPU-assisted Scalable Bayesian Gaussian Graphical Models with Application to Genome-wide Genetic Networks."
[5] "Repulsive Reciprocal Graphical Models with Application to Breast Cancer Subtyping."
[4] "Big Data Clustering and Classification with Non-conjugate Bayesian Nonparametric Models."
[3] "Bayesian Mixed Reciprocal Graphical Models with Application to Omni-platform Networks."
[2]
"Scalable Covariate-dependent Gaussian Graphical Models.''
[1] "ZODIAC2: A Comprehensive Depiction of Pan-Cancer Genetic Regulation."

Publications and Preprints

[13] Ni, Y., Müller, P.
, Shpak M.
, and 
Ji, Y.
 "Parallel-Tempered Feature Allocation for Large-scale Tumor Heterogeneity with Deep Sequencing Data." Submitted.
[12] Ni, Y., Müller, P., Lin, W., and Ji, Y. "Bayesian Graphical Models for Computational Network Biology." BMC Bioinformatics (in press).
[11] Ni, Y., and Müller, P. (2017), Discussion of "Sparse Graphs Using Exchangeable Random Measures." by Caron, F., and Fox, E. Journal of the Royal Statistical Society: Series B[arxiv]
[10] Ni, Y., Stingo, F. C., Ha, M. J., Akbani, R., and Baladandayuthapani, V. "Bayesian Hierarchical Varying-sparsity Model with Application to Cancer Proteogenomics." Journal of the American Statistical Association (in press)[app]
[9] Shpak M., Ni, Y., Lu, J., Müller, P. "Variance in Estimated Pairwise Genetic Distance Under High versus Low Coverage Sequencing: the Contribution of Linkage Disequilibrium." Theoretical Population Biology (in press)[biorxiv]
[8] Ni, Y., Müller, P., Zhu, Y., and Ji, Y. "Heterogeneous Reciprocal Graphical Models." Biometrics (in press). [arxiv]
[7] Ni, Y., Ji, Y., and Müller, P. "Reciprocal Graphical Models for Integrative Gene Regulatory Network Analysis." Bayesian Analysis (in press)[arxiv]
[6] Ni, Y., Stingo, F. C., and Baladandayuthapani, V., "Bayesian Graphical Regression.'' Journal of the American Statistical Association (in press). [link] [app]
[5] Ni, Y., Stingo, F. C., and Baladandayuthapani, V. (2017), "Sparse Multi-dimensional Graphical Models: A Unified Bayesian Framework.'' Journal of the American Statistical Association, 112(518) 779-793 [link]
[4] Guo, W., Ni, Y., and Ji, Y. (2015), "TEAMS: Toxicity- and Efficacy-based Dose Insertion Design with Adaptive Model Selection for Phase I/II Dose-Escalation Trials in Oncology." Statistics in Biosciences, 7(2) 432-459. [link]
[3] Ni, Y., Stingo, F.C., and Baladandayuthapani, V. (2015), "Bayesian Nonlinear Model Selection for Gene Regulatory Networks." Biometrics, 71(3) 585-595. [link]
[2] Ni, Y., Marchetti, G. M., Baladandayuthapani, V, and Stingo, F. C. (2015), "Bayesian Approaches for Large Biological Networks.'' in Nonparametric Bayesian Methods in Biostatistics and Bioinformatics, Mitra, R. and Müller, P. (eds), Springer-Verlag. [link]
[1] Ni, Y., Stingo, F. C., and Baladandayuthapani, V. (2014), "Integrative Bayesian Network Analysis of Genomic Data.'' Cancer Informatics, 13(s2) 39-48. [link]

Awards

[11] Travel Support, Rising Stars Symposium in Data Science, The University of Chicago, 2017
[10] Savage Award (honorable mention), Best Bayesian Dissertations, 2017
[9] Travel Support, The Third Annual Kliakhandler Conference on Bayesian Inference in Statistics and Statistical Genetics, 2017
[8] Junior Travel Support, 19th Meeting of New Researchers in Statistics and Probability, 2017
[7] Junior Travel Support, CBMS: Regional Conference on Spatial Statistics, 2017
[6] Young Researcher Award, The 10th ICSA International Conference, 2016
[5] Student Paper Award, The Section on Statistical Learning and Data Mining (SLDM) of the American Statistical Association (ASA), JSM 2016.
[4] NSF Junior Travel Support, ISBA World Meeting, Sardinia, Italy, 2016
[3] Jiann-Ping Hsu Pharmaceutical and Regulatory Sciences Award, Joint 24th ICSA Applied Statistics Symposium and 13th Graybill Conference, 2015.
[2] Young Investigator Travel Support, G70 Conference, Durham, North Carolina, 2015.
[1] Laplace Award (co-winner), top paper among the student travel award winners, The Section on Bayesian Statistical Science (SBSS) of the American Statistical Association (ASA), JSM 2014.

Thesis

Bayesian graphical models for complex biological networks (Savage award honorable mention)

Last updated: 01/2018