Yanchenko, E. (2025) Graph sub-sampling for divide-and-conquer algorithms in large networks, Statistics and Computing, 35, 87. https://doi.org/10.1007/s11222-025-10620-y
Yanchenko, E., Bondell, H.D. and Reich, B.J. (2025) The R2D2 Prior for Generalized Linear Mixed Models, The American Statistician, 79 (1), 40-49. https://doi.org/10.1080/00031305.2024.2352010
Yanchenko, E., Chappell, T.M. and Huseth, A.S. (2025) Bayesian Optimization of Insect Trap Distribution for Pest Monitoring Efficiency in Agroecosystems, Frontiers in Insect Science, 4, 1509942. https://doi.org/10.3389/finsc.2024.1509942
Yanchenko, E. (2024+) Statistics, in Introducing the Liberal Arts: A Guidebook for English Learners, Information Age Publishing, In Press.
Yanchenko, E., Murata, T. and Holme, P. (2024) Influence maximization on temporal networks: a review, Applied Network Science, 9, 16. https://doi.org/10.1007/s41109-024-00625-3
Yanchenko, E. and Sengupta, S. (2024) A generalized hypothesis test for community structure in networks, Network Science, 12 (2), 122-138. https://doi.org/10.1017/nws.2024.1
Yanchenko, E., Bondell, H.D. and Reich, B.J. (2024) Spatial regression modeling via the R2D2 framework, Environmetrics, 35 (2), e2829. http://doi.org/10.1002/env.2829
Yanchenko, E., Murata, T. and Holme, P. (2023) Link prediction for ex ante influence maximization on temporal networks, Applied Network Science, 8, 70. doi.org/10.1007/s41109-023-00594-z
Swaminathan, A.C., Snyder, L.D., Hong, H., Stevens, S.R., Long, A.S., Yanchenko, E., Qiu, Y., Liu, R., Zhang, H., Fischer, A., Burns, L., Wruck, L., Palmer, S.M. (2023) Generalizability of External Clinical Trial and Electronic Health Record Control Arms in Idiopathic Pulmonary Fibrosis. American Journal of Respiratory and Critical Care Medicine, 208 (5), 579-588.https://doi.org/10.1164/rccm.202210-1947OC
Yanchenko, E. and Sengupta, S. (2023) Core-periphery structure in networks: a statistical exposition, Statistics Surveys, 17, 42-74. https://doi.org/10.1214/23-SS141
Yanchenko, E. (2022) A divide-and-conquer algorithm for core-periphery identification in large networks. Stat. pp. e475. https://doi.org/10.1002/sta4.475
In review
Yanchenko, E. and Sengupta, S. (2025+) A label-switching algorithm for fast core-periphery identification, arXiv link: http://arxiv.org/abs/2506.02069
Yanchenko, E., Sengupta, S. and Mukherjee, D. (2025+) Statistical inference of core-periphery structures (under review).
Feng, B.R., Yanchenko, E., Hill, K.L., Rosman, L.A., Reich, B.J. and Rappold, A.G. (2024+) Mediation analysis of community context effects on heart failure using the survival R2D2 prior, Journal of the Royal Statistical Society: Series C (reject and resubmit), arXiv link: https://arxiv.org/abs/2411.04310
Yanchenko, E. (2024+) Oral exams in introductory statistics class with non-native English speakers, Teaching Statistics (major revisions), arXiv link: https://arxiv.org/abs/2409.16613
Yanchenko, E., Irie, K. and Sugasawa, S. (2024+) The Group R2D2 Shrinkage Prior for Sparse Linear Models with Grouped Covariates, arXiv link: arxiv.org/abs/2412.15293
Grants
KAKENHI Grant-in-Aid for Research Activity Start-up, The R2D2 Shrinkage Prior for Grouped Sparse Linear Models, Principal Investigator, Japan Society for the Promotion of Science, 1,430,000 yen, 2024-2025 (link)
Presentations
BOPIM: Bayesian Optimization for influence maximization on temporal networks, CCSS Workshop on Computational Social Science: Methods and Applications, Kobe University, Kobe, Japan, 2024 (invited)
Graph sub-sampling for divide-and-conquer algorithms in large networks, Economics Workshop, Keio University, Tokyo, Japan, 2024 (invited)
Core-periphery hypothesis testing in networks, Faculty of Economics, The University of Tokyo, Tokyo, Japan, 2024 (invited)
The R2D2 prior for generalized linear mixed models, 6th International Conference on Statistics and Econometrics (EcoSta 2023), Waseda University, Tokyo, Japan, 2023
Spatial regression modeling via the R2D2 framework, Workshop on Bayesian Statistics and Econometrics, Temple University Japan, Tokyo, Japan, 2023 (invited)
Comparing Bayesian methods for combining multiple historical controls in clinical trials, Annual Meeting of the Japanese Society of Biometrics, Sapporo, Japan, 2023
The R2D2 prior for generalized linear mixed models, Faculty of Economics, The University of Tokyo, Tokyo, Japan, 2023(invited)
A generalized hypothesis test for community structure in networks, Center for Computational Social Science, Kobe University, Kobe, Japan, 2023 (invited)
A divide-and-conquer algorithm for core-periphery identification in large networks, North Carolina State University, Raleigh, NC, 2022 (invited)
A divide-and-conquer algorithm for core-periphery identification in large networks (poster), SRCOS Summer Research Conference, Jekyll Island, GA, 2022
A generalized hypothesis test for community structure and homophily in networks, Sunbelt 2022, International Network for Social Network Analysis, Cairns, Australia, 2022.
Quantifying the presence/absence of meso-scale structures in networks, North Carolina State University, Raleigh, NC, 2022.
A model-agnostic hypothesis test for community structure and homophily in networks (poster), SRCOS Summer Research Conference, Jekyll Island, GA, 2021. Poster link. (won best graduate student poster)
A model-agnostic hypothesis test for community structure and homophily in networks, Joint Statistical Meeting, Seattle, WA, 2021. Recording link. Slides link.
Big Data Summer Institute Symposium and Poster Presentation, Department of Biostatistics, University of Michigan, 2018. Poster link.
Physics Publications
Asel, T., Yanchenko, E., Yang, X., Jiang, S., Krymowski, K., Wang, Y., Trout, A., McComb, D., Windl, W., Goldberger, J., Brillson, L., (2018) Identification of Ge Vacancies as Electronic Defects in Methyl- and Hydrogen-Terminated Germanane, Applied Physics Letters, 113, 061110.
Jiang, S., Krymowski, K., Asel, T., Arguilla, M., Cultrara, N., Yanchenko, E., Yang, X., Brillson, L., Windl W., Goldberger, J.G., (2016) Tailoring the Electronic Structure of Covalently Functionalized Germanane via the Interplay of Ligand Strain and Electronegativity, Chemistry of Materials, 28, 8071-8077.