Student research supervised by Edward Ionides

Undergraduate research projects

• Murat Ahmed. Modeling cholera as a stochastic process. Summer project, 2005.
• Xiaoai Chai. Building POMP objects in R for a dynamic general stochastic equilibrium model . Summer project, 2011.
• Cong Zhang. Investigating sequential Monte Carlo methods for time series analysis . Summer project, 2012.
• Xi Wu and Kelly Schmidt. Identification of insurance companies at risk of insolvency . Summer project, 2014.
• Hwanwoo Kim. Topics in design and analysis of clinical trials for adaptive treatment plans . Honors thesis, 2015. Winner of the departmental honors thesis award, and 2nd prize winner in the national Undergraduate Statistics Project Competition.
• Rebecca Mukena Yumba. Poliovirus Transmission Between Children, Teenagers and Adults: A Partially Observed Markov Process Analysis . Undergraduate Research Opportunity Program project, 2015-2016.
• Haoran Chen. Modeling and inference for polio transmission. Research project, 2017.
• Yichen Zhang, Environmental drivers of diarrheal infection. Research project, 2017.
• Xiaotong Yang. Fitting mechanistic models to Daphnia panel data within a panelPOMP framework. Honors thesis, 2018.
• Isabella Gierlinger and William Smith. Inference from viral genomes. Research project, 2019.
• Yiyang Nan and Allister Ho. Modeling and data analysis for spatiotemporal epidemiology. Research project, 2020.
• Chao Peter Yang. The classical-romantic dichotomy: A machine learning approach. Honors thesis, co-advised with Daniel Forger, 2021.
• Anna Rosengart and Andy Gu. Spatiotemporal epidemiology of dengue virus and the curse of dimensionality for Monte Carlo methods. Research project, 2021.
• Anna Rosengart. Modelling the 2010-2019 Haiti Cholera Epidemic. Honors thesis, 2021.
• Mingxuan Ge. Redistribution of Equity Returns After The Minimum Wage Policy. Honors thesis, co-advised with Florian Gunsilius, 2022.
• Kevin Tan and Noah Treutle. On the Transmissibility of Cholera During the 2010-2019 Haiti Cholera Epidemic. Research project, 2022.
• Yize Hao and Mingyuan Li. Modeling Measles in Multiple Cities. Research project, 2023.
• Bo Yang. Analysis of Panel Data via Mechanistic Models in a PanelPOMP Framework. Honors thesis, 2023.
• Kevin Tan. Differentiable Plug-and-Play Particle Filtering. Honors thesis, 2023.
• Zuyuan Han. Signature Methods in Variance Swap Pricing. Honors thesis, 2023.

Masters research projects

• Rui Zhang. Modeling Fraser River salmon abundance . Research project, 2015.
• Jifan Li. Spatiotemporal modeling and inference for COVID-19. Research project, 2022.

PhD students

• Carles Breto. Statistical inference for nonlinear dynamical systems, 2007.
• Anindya Bhadra. Time series analysis for nonlinear dynamical systems with applications to modeling of infectious diseases, 2010.
• Zhen Wang. Topics in time series analysis with macroeconomic applications, 2012.
• Dao Nguyen. Iterated filtering and smoothing with application to infectious disease models, 2016.
• Alex Smith. Inference of infectious disease dynamics from genetic data via Sequential Monte Carlo, 2018. Jointly supervised with Aaron King.
• Joon Ha Park. Computational Inference Algorithms for Spatiotemporal Processes and Other Complex Models, 2018.
• Tim NeCamp. Design and Analysis of Sequential Randomized Trials with Applications to Mental Health and Online Education, 2019. Jointly supervised with Zhenke Wu.
• Kidus Asfaw. Simulation-based Inference for Partially Observed Markov Process Models with Spatial Coupling, 2021. Jointly supervised with Aaron King.

Postdocs

• John Marino. NSF postdoctoral fellowship on Enhancement of ecological inference and forecasting, with applications to critical threats facing Great Lakes fisheries, 2015-2017. Jointly supervised with Scott Peacor.
• Carles Breto. NIH-funded project on X-Raying High-Dimensional Infectious disease as part of the Center for Inference and Dynamics of Infectious Diseases. 2015-2018. Jointly supervised with Aaron King.
• Kevin Bakker. NIH postdoctoral fellowship on Uncovering the mechanisms driving seasonal polio incidence: A modeling approach towards endgame strategies. 2018-2020. Jointly supervised with Mercedes Pascual.
• Patricia Ning. NSF and NIH funded project on Urban vector-borne disease transmission demands advances in spatiotemporal statistical inference. 2019-2022.
• Qianying Lin. Michigan Institute for Data Science Institute fellowship on phylodynamic inference with applications to epidemiology. Jointly supervised with Aaron King. 2019-2021.
• Brandon Legried. NSF postdoctoral fellowship on Understanding dynamic big data with complex structure. Jointly supervised with Jonathan Terhorst. 2019-2021.