Photograph by Marc-Grégor Campredon

**Complexity: From Simple Rules to Complex Behavior**(Complex Systems 100), University of Michigan, Ann Arbor – this course covers a broad range of introductory topics in complex systems, exploring how the tools and ideas of complex systems can help us understand the world around us.

**Computational Modeling of Complex Systems**(Complex Systems 530), University of Michigan, Ann Arbor – an introduction to computational approaches to complex systems, particularly focused on agent-based models, as well as cellular automata, network models, sensitivity analysis, and other topics. (previous versions: 2020, 2021, 2022, 2023)

**Introduction to Complex Systems Modeling for Public Health**(Epid 793), University of Michigan, Ann Arbor – a summer short-course intensive introduction to complex systems/math modeling in public health.

**Advanced Modeling Methods**(Epid 814), University of Michigan, Ann Arbor – graduate course in mathematical modeling methods and working with data, including parameter estimation approaches (such as maximum likelihood and Bayesian methods), uncertainty quantification, stochastic models, topics from dynamical systems, data scraping, data visualization, and basics of machine learning. (previous versions: 2017, 2019)

**Introduction to Mathematical Modeling in Epidemiology & Public Health**(Epid 633), University of Michigan, Ann Arbor – basic introduction to math modeling in epidemiology, with examples drawn broadly from infectious disease, chronic disease, and social epidemiology.

**Systems Modeling of Social Processes, Behavior, and Chronic Disease**(Epid 637), University of Michigan, Ann Arbor – complex system modeling of chronic diseases and social behavior processes, using agent-based, network models, and dynamic system models.**Scientific Communication for Epidemiologists**(Epid 530), University of Michigan, Ann Arbor – overview of scientific writing and communication.**Foundations of Higher Mathematics**(Math 345), The Ohio State University (Fall 2010) – this course introduces students (primarily math majors) to basic proof techniques, logic, and set theory.

**R workshops at the Washtenaw County Health Department**(2023) - intro to R, data wrangling, tidyverse and dplyr, ggplot2, automation and data pipelines in R, Quarto and document creation in R**R workshop at the Michigan Department of Health and Human Services**(2023) - intro to R, data wrangling, tidyverse and dplyr, ggplot2, automation in R, intro to APIs and the RSocrata package**NC State Parameter Estimation Tutorial Workshop**(2019) Identifiability lecture and lab (previous versions: 2018)

**Colorado School of Mines Tutorial**(2019) - identifiability and parameter estimation**BWF PUP iTiMS Workshop 2017**- Workshop Exercise Instructions
- Github repository - this contains the files for the exercise.
- Observation Form - use this to record your answers and observations as you go.
- Afternoon Exercise Observation Form - NetLogo Exercises

**NC State Tutorial Workshop on Parameter Estimation for Biological Models**(Summer 2014). Taught a 1-day tutorial on structural and practical identifiability.**NIMBioS Tutorial Workshop: Parameter Estimation for Dynamic Biological Models**(Summer 2014). A three-day tutorial based at the National Institute for Mathematical and Biological Synthesis, University of Tennessee.**NIMBioS-MBI-CAMBAM Summer Graduate Program: Connecting Models with Data in Mathematical Biology**(Summer 2013). A two-week summer graduate program based at the National Institute for Mathematical and Biological Synthesis, University of Tennessee.**Michigan Math & Science Scholars Program**– (guest lecturer) math and science program for advanced high school students. (Summer 2013)**Nonlinear Dynamics in Biological Networks, McGill University**(Summer 2010) - developed and taught a series of labs and research projects on symmetry and networks for the joint CAMBAM/MBI summer school (together with Yunjiao Wang and Marty Golubitsky).