Yesha Patel, Ph.D. 2023, Applications of causal inference methods for the estimation of effects of prescription drugs and bone marrow transplant on survival of aplastic anemia patients.
Albert Pierce, Ph.D. 2023. Causal inference and machine learning methods in Parkinson’s disease data analysis.
Ehsan Yaghmaei, Ph.D. 2023. Causal inference methods for estimation of survival and general health measures for Alzheimer’s disease patients.
Hanna Lu, Ph.D. 2022. Advances in natural language processing algorithms on unstructured medical notes data and approaches to handling class imbalance issues.
Arin Ghazarian, Ph.D. 2021. Assessing the re-identification risk in ECG datasets and an application of privacy preserving techniques in ECG analysis.
Jianwei Zheng, Ph.D. 2021. Optimal analytical methods for high accuracy cardiac disease classification and treatment based on ECG data.
Alex Barrett, Ph.D. 2020. Forecasting the prices of cryptocurrencies using a novel parameter optimization of VARIMA models.
Sidy Danioko, Ph.D. 2020. Advances in financial time series analysis, imputation methods accuracy and risk factors for ED readmission and prolonged hospital length of stay.
Chris Watkins, Ph.D. 2020. Novel statistical and machine learning methods for the forecasting and analysis of Major League Baseball player performance.
Kyle Anderson, Ph.D. 2019. Contributions to variable selection in complexly sampled case-control studies with survey data, estimation of combined migration and mortality rates of limpets using pseudo-tagged longitudinal data and epidemiology of return visits to emergency department within 72 hours.
Michael Schwartz, Ph.D. 2017. Optimized forecasting of dominant U.S. stock market equities using univariate and multivariate time series analyses methods.
Louis Ehwerhemuepha, Ph.D. 2015. Contributions to nonparametric methods, stepwise model selection algorithms in logistic regression and epidemiology of general pediatric hospital readmissions.
Current Ph.D. students in alphabetical order:
Eric Adams
Omer Odabas
Duncan Ofosu
Reza Rezai
Ryan Richardson
David Licerio, M.S. 2024. Predicting 30-day unplanned ICU readmissions using deep learning and natural language processing techniques: a MIMIC IV data analysis.
Minhao Huang, M.S. 2024. A novel correction for the multivariate Ljung-Box test.
Gregory Tyler, M.S. 2023. Novel implementation of additive manufacturing to visualize the human brain connectome.
Joshua Anderson, M.S. 2022. CausalModels: An R library for estimating causal effects.
Richard Beuttler, M.S. 2016. Comparison of gait pattern progression of infants born full term and preterm using linear mixed effects models.
Alex Leipf, M.S. 2015. An analysis of hybrid vehicle sales success using stepwise linear mixed effects modeling.