Tyler Cook

Tyler Cook

Research

My main research interests are in survival analysis focusing on interval-censored data, informative censoring, and variable selection. I am also interested in longitudinal data analysis, data mining and statistical learning, deep learning, and sports statistics.

While at the University of Missouri, I consulted for members of an evolutionary biology lab, and for a psychologist studying autism. At the University of Central Oklahoma, I work with groups of undergraduates undertaking consulting work as part of Project SCHOLAR.

Selected Publications

  • Fogarty, E., Tabatabai, S., Hendryx Lyons, E.P., and Cook, T. (2026). Recurrent Variational Autoencoder Beat Classification in Multi-Lead Electrocardiogram Data. 48th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Accepted.
  • Cook, T., Brumley, D., and Chakraborty, S. (2026). Using Guided Regularized Random Forests to Identify Important Biological Pathways and Genes. Big Data Analytics in Biostatistics and Bioinformatics, Editors: Zhao, Y. and Chen, D.G., Springer, Cham.
  • Crockett, K., Langer, A., Cook, T., and Hendryx Lyons, E.P. (2026). Comparing Subset Selection Methods in Multi-Lead Electrocardiogram Data. Network Modeling Analysis in Health informatics and Bioinformatics, 15(1), 51.
  • Cook, T. (2025). The Advantage of Moving First in Amateur Online Chess. ICGA Journal, 46:(3-4), 112-120.
  • Cook, T., Ma, K., and Hendryx Lyons E. (2024). Evaluating Heartbeat Segmentation Methods for the Analysis of Electrocardiogram Data. JSM Proceedings, https://doi.org/10.5281/zenodo.13916371.
  • Ali, S., Cook, T., Ewaid, S., and Gamagedara, S. (2023). Development of a Water Quality Index Using Sparse Principal Component Analysis for the Tigris River in Iraq. Water Resources, 50: 152-167.
  • Dunn, T., Cook, T., and Hendryx, E. (2022). A Comparison of Deep Learning Methods for Identifying Anomalous Heartbeats in Electrocardiogram Data. JSM Proceedings, Statistical Computing Sections, Alexandria, VA: American Statistical Association.
  • Nichols, C., and Cook, T. (2022). Estimating Aircraft State from Surveillance Data Using Statistical Learning. AIAA Aviation 2022 Forum, https://doi.org/10.2514/6.2022-3424.
  • Cook, T., Ma, Y., and Gamagedara, S. (2020). Evaluation of Statistical Techniques to Normalize Mass Spectrometry-Based Urinary Metabolomics Data. Journal of Pharmaceutical and Biomedical Analysis, 177: 112854.
  • Lee, R.J., Huggins, A., Waters, A., Eitrheim, E.S., and Cook, T. (2019). Analyzing Factors for First Semester General Chemistry Student Success at the University of Central Oklahoma. Proceedings of the Oklahoma Academy of Sciences, 99: 120-125.
  • Fu, J., Li, F., Ong, M., Cook, T., Qian, G., and Zhao, Y.D. (2018). A Novel Approach for Assessing Power Wheelchair Users’ Mobility by Using Curve Fitting. Duffy V. (eds) Digital Human Modeling. Applications in Health, Safety, Ergonomics, and Risk Management. DHM 2018. Lecture Notes in Computer Science, vol 10917. Springer, Cham.
  • Cook, T., Zhang, Z., and Sun, J. (2017). Simulation Studies on the Effects of the Censoring Distribution Assumption in the Analysis of Interval-censored Failure Time Data. Monte-Carlo Simulation-Based Statistical Modeling, Editors: Chen, D.G. and Chen, J.D., Springer, 319-346.

Selected Presentations

  • Using Variational Autoencoders to Identify Noise in Electrocardiogram Data. Joint Statistical Meetings, Boston, MA, August 2026.
  • Evaluating Heartbeat Segmentation Methods for the Analysis of Electrocardiogram Data. Joint Statistical Meetings, Portland, OR, August 2024.
  • Using Clustering to Analyze Positions in Professional Basketball Through Different Eras. Symposium on Data Science and Statistics, St. Louis, MO, May 2023.
  • Changes in Undergraduate Attitudes Towards Statistics After Working as Statistical Consultants. Joint Statistical Meetings, Washington D.C., August 2022.
  • Pathway and Gene Selection with Guided Regularized Random Forests. ICSA 2018 Applied Statistics Symposium, New Brunswick, NJ, June 2018.
  • Transforming Undergraduate Statistics Education at Primarily Undergraduate Institutions through Experiential Learning. 2017 Joint Mathematics Meetings, Atlanta, GA, January 2017.
  • Variable Selection for Interval-censored Survival Data Under the Proportional Hazards Model. ICSA 2016 Applied Statistics Symposium, Atlanta, GA, June 2016.
  • Model Flexibility for Regression Analysis of Survival Data with Informative Interval Censoring. ENAR 2015 Spring Meeting, Miami, FL, March 2015.

Selected Student Presentations

  • Class Detection with Oversampling Methods. Joint Statistical Meetings, Boston, MA, August 2026. Presented by A. Davis.
  • Detecting Noise in Multi-Lead Electrocardiogram Data with Deep Learning. Joint Statistical Meetings, Boston, MA, August 2026. Presented by S. Tabatabai and E. Pendleton.
  • Contrasting Subset Selection Methods in Multilead Electrocardiogram Data. Joint Statistical Meetings, Portland, OR, August 2024. Presented by K. Crockett and A. Langer.
  • A Comparison of Multi-Lead ECG Arrhythmia Detection Methods Using Variational Autoencoders. Joint Statistical Meetings, Portland, OR, August 2024. Presented by E. Fogarty and K. Hallmark.
  • Statistical Learning Approaches to Heartbeat Classification. Symposium on Data Science and Statistics, St. Louis, MO, May 2023. Presented by Z. Johnson and E. Noble.
  • Subset Selection Methods for Summarizing Electrocardiogram Data. Symposium on Data Science and Statistics, St. Louis, MO, May 2023. Presented by N. Holt and A. Langer.
  • A Comparison of Deep Learning Methods for Identifying Anomalous Heartbeats in Electrocardiogram Data. Joint Statistical Meetings, Washington D.C., August 2022. Presented by T. Dunn.
  • Estimating Aircraft State from Surveillance Data Using Statistical Learning. AIAA Aviation Forum, Chicago, IL, June 2022. Presented by C. Nichols.
  • Comparison of NBA Personal Fouls. Oklahoma Research Day, Virtual, March 2021. Presented by Y. Kim.
  • An Imputation Approach for Fitting Random Survival Forests with Interval-Censored Survival Data. Joint Statistical Meetings, Denver, CO, July 2019. Presented by W. Keil.
  • Metacognitive Studying Strategies and Student Success in General Chemistry. National Council of Undergraduate Research, Kennesaw, GA, April 2019. Presented by A. Huggins and R.J. Lee.
  • A Tale of Two Models: A Non-Spatial and Spatial Regression Analysis of Poverty in Oklahoma. Oklahoma Research Day, Weatherford, OK, March 2019. Presented by E. Ojeda.
  • Evaluating Whether Expert Rankings on Fantasy Basketball Players are Accurate. Oklahoma Research Day, Weatherford, OK, March 2019. Presented by S. Deng.
  • Determining What Individual and Household Factors Influence Food Choice. Oklahoma Research Day, Weatherford, OK, March 2019. Presented by W. Kouadio.
  • Techniques for Providing Optimal Regulation Levels for Injection Wells in Oklahoma. National Council for Undergraduate Research, Edmond, OK, April 2018. Presented by W. Cranford.
  • Evaluating Whether Online Reviews Influence Airline Choice. National Council for Undergraduate Research, Edmond, OK, April 2018. Presented by A. Kouadio.
  • Determining Factors for Elderly Independent Living. National Council for Undergraduate Research, Memphis, TN, April 2017. Presented by E. Kelting, L. Lerma, and D. Seagle.