Researcher Details

Basic Information

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Eric YANCHENKO

Nationality	UNITED STATES
Research Fields, Keywords	Statistics, Networks, Bayesian, Data Science
Homepage URL	http://www.ericyanchenko.com

Profile

I'm glad you found my profile! I'm an assistant professor of AI and data science at AIU where I have been since 2024.

I completed by undergraduate studies at The Ohio State University in 2019 with a double major in mathematics and physics. Immediately after graduation, I began a PhD in statistics at North Carolina State University where I was advised by Brian Reich and Srijan Sengupta. In 2023, I spent seven months at Tokyo Institute of Technology on a JSPS fellowship working with Petter Holme and Tusyoshi Murata. I finished my PhD in 2023 and started at AIU in 2024.

Research Field

I have two main research interests which recently have found some overlap. First, I study networks. Networks are a simple way to represent complex relationships between entities. I consider well-known network structures, e.g., community and core-periphery, and seek to formalize them from a statistical angle.

Second, I am interested in Bayesian inference, particularly in deriving principle prior distributions for scale parameters in hierarchical models. It is a well-known challenge to elicit priors for scale parameters, and I have applied my work to generalized linear mixed models and spatial regression models. Recently, I have also been interested in Bayesian Optimization (BO), a paradigm for optimizing complicated objective functions. I have applied this work to the influence maximization (IM) problem in network science, and can be applied to many other interesting domains.

Recent Activities

Please see my website or Google Scholar for a complete list of publications.

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Academic Background (Undergraduate Level) 【 display / non-display 】

The Ohio State University, Columbus, OH, USA, Faculty of Arts and Science, Mathematics and Physics

University, 2019/05, Graduated, UNITED STATES

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Academic Background (Graduate Level) 【 display / non-display 】

North Carolina State University, Graduate School, Division of General Science, Statistics

Doctor's Course, 2023/12, Completed, UNITED STATES

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Field of Expertise 【 display / non-display 】

Statistical science

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Academic Papers 【 display / non-display 】

The R2D2 prior for generalized linear mixed models, The R2D2 prior for generalized linear mixed models, vol.79 (1) (p.40 - 49) , 2025, Eric Yanchenko, Howard D. Bondell, Brian J. Reich

DOI:10.1080/00031305.2024.2352010, Research paper (scientific journal), Multiple Authorship, English
Bayesian Optimization of Insect Trap Distribution for Pest Monitoring Efficiency in Agroecosystems, Bayesian Optimization of Insect Trap Distribution for Pest Monitoring Efficiency in Agroecosystems, vol.4, 2024/12, Eric Yanchenko, Thomas M. Chappell, Anders S. Huseth

DOI:10.3389/finsc.2024.1509942, Research paper (scientific journal), Multiple Authorship, English
Influence maximization on temporal networks: a review, Influence maximization on temporal networks: a review, vol.9 (16) (p.N/A) , 2024/05, Eric Yanchenko, Tsuyoshi Murata, Petter Holme

DOI:10.1007/s41109-024-00625-3 , Research paper (scientific journal), Multiple Authorship, English
A generalized hypothesis test for community structure in networks, A generalized hypothesis test for community structure in networks, vol.12 (2) (p.122 - 138) , 2024/03, Eric Yanchenko, Srijan Sengupta

DOI:10.1017/nws.2024.1, Research paper (scientific journal), Multiple Authorship, English
Spatial regression modeling via the R2D2 framework, Spatial regression modeling via the R2D2 framework, vol.35 (2) (p.e2829 - N/A) , 2023/10, Eric Yanchenko, Howard D. Bondell, Brian J. Reich

DOI:10.1002/env.2829, Research paper (scientific journal), Multiple Authorship, English

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Books 【 display / non-display 】

Introducing the Liberal Arts: A Guidebook for English Learners, Emerald Publishing, 2025, Cherie Brown, James Reid, Malcolm Sim, Clay Williams

Textbook, Multiple Authorship , English

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Grant-in-Aid for Scientific Research 【 display / non-display 】

Grant-in-Aid for Research Activity Start-up，2024/07 - 2026/03，The R2D2 Shrinkage Prior for Grouped Sparse Linear Models

The goal of this project is to develop a novel shrinkage prior model for the sparse grouped regression setting by leveraging the R2D2 prior framework.