Han Yu, Ph.D.
Associate Professor
Applied Statistics and xxx直播 Methods
Education and Behavioral xxx直播s
Contact Information
Mailing Address
University of Northern Colorado
Applied Statistics and xxx直播 Methods
Campus Box 124
Greeley, CO 80639
Education
- Ph.D. in Statistics, Department of Statistics, Florida State University
- MS in Statistics, Department of Statistics, Florida State University
- MS in Probability and Statistics, Department of Mathematics, Xiamen University
- BS in Pure Mathematics, Department of Mathematics, Xiamen University
Professional/Academic Experience
Joined the University of Northern Colorado (UNC) in 2017. After completing Ph.D.,
I taught and developed a variety of statistics and data science courses at universities
in the USA, catering to a wide range of academic levels, from undergraduate to doctoral
students. At UNC, I am dedicated to teaching both statistics and data science courses,
engaging in scholarship, and advising master鈥檚 and Ph.D. students on research projects
that primarily focus on kernel-based semiparametrics and double machine learning,
methodologies that are crucial in the contemporary field of causal inference and missing
data.
Graduate Courses Taught in UNCO:
xxx直播/Areas of Interest
I have established a research program focused on modeling, reasoning, inference, discovery,
and interpretation of the latent mechanisms underlying complex, high-dimensional network
data. Rooted in contemporary measure-theoretic probabilistic reasoning theory, my
work explores the functional spaces of probability measures through a minimax coherent
paradigm. I have actively pursued various opportunities for interdisciplinary collaborative
research projects. These projects largely rely on measure-theoretically sound methodologies
and leverage advanced ML/AI algorithms for structural causal learning and discovery.
I have cultivated insights into a unified measure-theoretic approach to causal inference.
This approach leverages functional analysis for product measure-theoretic reasoning
applied to random objects in spaces of functions associated with functional co-occurrence
data, an expertise fortified through extensive engagement with multidisciplinary research.
My research interests span the following areas:
- Modern Causal Inference and Discovery
- Structural/Functional Causal Models
- Bayesian Nonparametrics
- SPDE-based Spatio-Temporal Statistics
- Hierarchical Latent Variable Models
- Measure-Theoretic Graphical Models
- Network Computational Statistics and High-Performance Computing
- Empirical Processes Theory
- Stochastic Processes
Publications/Creative Works
- Rathke, B.H., Yu, H. and Huang, H. (2023) What is left now that fear is gone? Data
mining and analysis of COVID-19 pandemic emotions using Twitter, Google Trends, and
Public Health data. Disaster xxx直播 and Public Health Preparedness, 17, E471.
- Agboola, D. O. and Yu, H. (2023) Neighborhood-Based Cross Fitting Approach to Treatment Effects for High-Dimensional
Data. Computational Statistics & Data Analysis, 186, 107780.
- Huang, H. and Yu, H. and Li, W. (2023) Using Technology Acceptance Model to Analyze
the Successful Crowdfunding Learning Game Campaigns. Information Technologies and Learning Tools, 95(3), 25-40
- Owusu, G., Yu, H. and Huang, H. (2022) Temporal dynamics for areal unit-based co-occurrence
COVID-19 trajectories. AIMS Public Health, 9(4), 703-717.
- Oduro, M. S., Yu, H. and Huang, H. (2022) Predicting the Entrepreneurial Success of Crowdfunding Campaigns Using Model-based
Machine Learning Methods. International Journal of Crowd xxx直播, 6(1), 7-16.
- Shi, T., Yu, H., Lim, C.L. (2021) Consumer affinity and an extended view of the spillover
effects of attitudes toward a cross-border-acquisition event. Journal of Brand Management, 28, 596-608.
- Yu, H., Jiang, S., and Huang, H. (2021) Spatio-Temporal Parse Network-Based Trajectory
Modeling on The Dynamics of Criminal Justice System. Journal of Applied Statistics, 49(8), 1979-2000.
- Wang, J.Y. and Yu, H. (2020) The Measure on the Original Space from A Product Measure. Journal of Mathematical Analysis and Applications, 491(1), 124272.
- Woods, C., Yu, H. and Huang, H. (2020) Predicting the Success of Entrepreneurial Campaigns in Crowdfunding:
A Spatio-Temporal Approach. Journal of Innovation and Entrepreneurship, 9(13), 1-23.
- Vetter, R. E., Yu, H., Foose, A. K., Adams, P. J. and Dodd, R. K. (2017) Comparison
of Training Intensity Patterns for Cardiorespiratory, Speed and Strength Exercise
Programs. Journal of Strength and Conditioning xxx直播, 31(12), 3372-3395, December 2017.
- Vetter, R. E., Yu, H., and Foose, A. K. (2017) The Effects of Moderators on Physical
Training Programs: A Bayesian Approach. Journal of Strength and Conditioning xxx直播, 31(7), 1868-1878. July 2017.
- Yu, H., Jiang, S., and Land, K. (2015) Multicollinearity in Hierarchical Linear Models.
Social xxx直播 xxx直播, 53, 118-136.
Honors and Awards
- 2021 NSF travel grant for NSF/CBMS xxx直播 Conference on Gaussian Random Fields, Fractals, SPDEs, and Extremes
- 2019 Best Award in model/analysis in the Symposium on Data xxx直播 & Statistics Data
Challenge
- 2016 Co-PI: MRI: Acquisition of the Bartik High-Performance Computing Cluster
- 2014 NSF Travel Award: the 3rd workshop on Biostatistics and Bioinformatics
-
Sponsors: GSU xxx直播 Foundation, National xxx直播 Foundation, Institution of Mathematical
Statistics, International Chinese Statistical Association and Department of Mathematics
and Statistics, Georgia State University
- 2009 Co-PI: The ASA/BJS Small Grants xxx直播 Program.
- Sponsors: American Statistics Association (ASA) and Bureau of Justice Statistics (BJS).
- Amount Funded: $29,517.00.
- 2006 First Class Prize of Student Paper Competition, Florida Chapter of the American Statistics Associate (ASA) Annual Meeting.
- 2000 Best first-year student in theoretical statistics, Department of Statistics, Florida State University.
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