HR job title
- Associate Professor
- Contact Info
- Websites
Ni, Yang Assistant Professor
Positions
- Assistant Professor, Statistics, College of Arts and Sciences
- Overview
- Publications
- Research
- Teaching
- Background
- Contact
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Overview
Publications
selected publications
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academic article
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Zhou, F., He, K., Cai, J. J., Davidson, L. A., Chapkin, R. S., & Ni, Y.
(2023).
A Unified Bayesian Framework for Bi-overlapping-Clustering Multi-omics Data via Sparse Matrix Factorization. Statistics in Biosciences.
15(3), 669-691.
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Zhou, F., He, K., Wang, K., Xu, Y., & Ni, Y.
(2023).
Functional Bayesian networks for discovering causality from multivariate functional data. Biometrics.
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Zhou, F., He, K., & Ni, Y.
(2023).
Individualized causal discovery with latent trajectory embedded Bayesian networks. Biometrics.
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Chen, S., He, K., He, S., Ni, Y., & Wong, R.
(2023).
Bayesian Nonlinear Tensor Regression with Functional Fused Elastic Net Prior. Technometrics.
ahead-of-print(ahead-of-print), 1-13.
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Niu, Y., Ni, Y., Pati, D., & Mallick, B. K.
(2023).
Covariate-Assisted Bayesian Graph Learning for Heterogeneous Data. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION.
ahead-of-print(ahead-of-print), 1-15.
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Wang, Z., Ni, Y., Jing, B., Wang, D., Zhang, H., & Xing, E.
(2022).
DNB: A Joint Learning Framework for Deep Bayesian Nonparametric Clustering. 33(12), 7610-7620.
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Zhou, F., He, K., Li, Q., Chapkin, R. S., & Ni, Y.
(2022).
Bayesian biclustering for microbial metagenomic sequencing data via multinomial matrix factorization. Biostatistics.
23(3), 891-909.
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Ni, Y., Mueller, P., & Ji, Y.
(2020).
Bayesian Double Feature Allocation for Phenotyping With Electronic Health Records. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION.
115(532), 1620-1634.
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Ni, Y., Ji, Y., & Mller, P.
(2020).
Consensus Monte Carlo for Random Subsets using Shared Anchors. Journal of Computational and Graphical Statistics.
29(4), 703-714.
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Vickman, R. E., Broman, M. M., Lanman, N. A., Franco, O. E., Sudyanti, P., Ni, Y., ... Hayward, S. W
(2020).
Heterogeneity of human prostate carcinoma-associated fibroblasts implicates a role for subpopulations in myeloid cell recruitment. The Prostate.
80(2), 173-185.
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Ni, Y., Mller, P., Diesendruck, M., Williamson, S., Zhu, Y., & Ji, Y.
(2020).
Scalable Bayesian Nonparametric Clustering and Classification. Journal of Computational and Graphical Statistics.
29(1), 53-65.
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Ni, Y., Ji, Y., & Mueller, P
(2019).
Consensus Monte Carlo for Random Subsets using Shared Anchors
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Ni, Y., Stingo, F. C., & Baladandayuthapani, V.
(2019).
Bayesian Graphical Regression. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION.
114(525), 184-197.
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Ni, Y., Stingo, F. C., Ha, M. J., Akbani, R., & Baladandayuthapani, V.
(2019).
Bayesian Hierarchical Varying-sparsity Regression Models with Application to Cancer Proteogenomics. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION.
114(525), 48-60.
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Ge, T., Chen, C., Ni, Y., Feng, Y., & Smoller, J. W.
(2019).
Polygenic prediction via Bayesian regression and continuous shrinkage priors. Nature Communications.
10(1), 1776.
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Ni, Y., Ji, Y., & Mueller, P.
(2018).
Reciprocal Graphical Models for Integrative Gene Regulatory Network Analysis. Bayesian Analysis.
13(4), 1091-1106.
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Ni, Y., Mueller, P., & Ji, Y
(2018).
Bayesian Double Feature Allocation for Phenotyping with Electronic Health Records
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Ni, Y., Mller, P., Zhu, Y., & Ji, Y.
(2018).
Heterogeneous reciprocal graphical models. Biometrics.
74(2), 606-615.
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Ni, Y., Mller, P., Wei, L., & Ji, Y.
(2018).
Bayesian graphical models for computational network biology. BMC Bioinformatics.
19(Suppl 3), 63.
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Caron, F., & Fox, E. B.
(2017).
Sparse graphs using exchangeable random measures. Journal of the Royal Statistical Society Series B: Statistical Methodology.
79(5), 1295-1366.
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Arbel, J., Battiston, M., Favaro, S., Lijoi, A., Prnster, I., Mena, R. H., Ni, Y., & Mller, P.
(2017).
Discussions of the paper "Sparse graphs using exchangeable random measures" by F. Caron and E. B. Fox
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Ni, Y., Stingo, F. C., & Baladandayuthapani, V.
(2017).
Sparse Multi-Dimensional Graphical Models: A Unified Bayesian Framework. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION.
112(518), 779-793.
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Shpak, M., Ni, Y., Lu, J., & Mller, P.
(2017).
Variance in estimated pairwise genetic distance under high versus low coverage sequencing: The contribution of linkage disequilibrium. Theoretical Population Biology.
117, 51-63.
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Ni, Y., Stingo, F. C., & Baladandayuthapani, V
(2015).
Bayesian nonlinear model selection for gene regulatory networks. Biometrics.
71(3), 585-595.
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Guo, W., Ni, Y., & 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.
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Ni, Y., Stingo, F. C., & Baladandayuthapani, V.
(2014).
Integrative bayesian network analysis of genomic data. Cancer Informatics.
13(Suppl 2), 39-48.
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Zhou, F., He, K., Cai, J. J., Davidson, L. A., Chapkin, R. S., & Ni, Y.
(2023).
A Unified Bayesian Framework for Bi-overlapping-Clustering Multi-omics Data via Sparse Matrix Factorization. Statistics in Biosciences.
15(3), 669-691.
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chapter
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Ni, Y., Marchetti, G. M., Baladandayuthapani, V., & Stingo, F. C.
(2015).
Bayesian Approaches for Large Biological Networks. NONPARAMETRIC BAYESIAN INFERENCE IN BIOSTATISTICS.
(pp. 153-173).
Springer Nature.
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Ni, Y., Marchetti, G. M., Baladandayuthapani, V., & Stingo, F. C.
(2015).
Bayesian Approaches for Large Biological Networks. NONPARAMETRIC BAYESIAN INFERENCE IN BIOSTATISTICS.
(pp. 153-173).
Springer Nature.
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conference paper
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Ni, Y., Jones, D., & Wang, Z
(2020).
Consensus Variational and Monte Carlo Algorithms for Bayesian Nonparametric Clustering. 204-209.
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Ni, Y., Mller, P., Shpak, M., & Ji, Y.
(2019).
Parallel-Tempered Feature Allocation for Large-Scale Tumor Heterogeneity with Deep Sequencing Data. Springer Proceedings in Mathematics and Statistics.
233-247.
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Ni, Y., Jones, D., & Wang, Z
(2020).
Consensus Variational and Monte Carlo Algorithms for Bayesian Nonparametric Clustering. 204-209.
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institutional repository document
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Chakrabarti, A., Ni, Y., Morris, E., Salinas, M. L., Chapkin, R. S., & Mallick, B. K.
(2023).
Graphical Dirichlet Process for Clustering Non-Exchangeable Grouped Data
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Ni, Y.
(2022).
Bivariate Causal Discovery for Categorical Data via Classification with Optimal Label Permutation
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Ni, Y., & Mallick, B.
(2022).
Ordinal Causal Discovery
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Chakrabarti, A., Ni, Y., Morris, E., Salinas, M. L., Chapkin, R. S., & Mallick, B. K.
(2023).
Graphical Dirichlet Process for Clustering Non-Exchangeable Grouped Data
Research
Teaching
teaching activities
- STAT211 Prin Of Statistics I Instructor
- STAT491 Research Instructor
- STAT636 Applied Multivariate Anly Instructor
- STAT639 Data Mining & Analysis Instructor
- STAT681 Seminar Instructor
- STAT685 Directed Studies Instructor
- STAT689 Sptp: Prob And Causal Graphs Instructor
- STAT689 Sptp:probabilistic Graphs Instructor
- STAT691 Research Instructor
Background
education and training
- Ph.D. in Statistics, Rice University - (Houston, Texas, United States) 2015
Contact
first name
- Yang
has last name
- Ni
Other
- y.ni@tamu.edu