Kenneth Mulder
Associate Professor of Data Analysis and Modeling
Kenneth Mulder is a former organic farmer and community organizer who has been working as a scientist and educator in the fields of data science, ecological economics, and applied mathematics for the last 20 years. He received a B.A. in mathematics from Kalamazoo College, an M.S. in mathematics from the University of Oregon, and a Ph.D. in ecological economics from the University of Vermont.
Mulder has used his skills as a statistician and modeler to conduct research in a variety of fields including analyzing renewable energy technologies, estimating the benefits of wetlands in reducing the damage from hurricanes, improving our understanding of the gut microbiome of ticks and the bacterium that causes Lyme disease, assessing the sustainable development of countries, and, most recently, modeling fractal growth in polymers.
He is most passionate about using data and mathematical models to better understand our interactions with the world and to address the gross inequities that exist in our societies. He believes data analysis and modeling are tools that can empower people to be agents of change. He is also very passionate about complex board games and has been using such games to teach math for over ten years. When not working as a scientist or educator, he is an active father of seven who enjoys family reading time.
Recent and Upcoming Courses
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Due to the growing availability of "big data" and the high computational speeds and storage capacity of modern computers, data science has become a highly influential field that impacts every aspect of our lives. Endeavors as disparate as facial recognition, climate modeling, and training computers to write poetry are linked by the fact that in each case researchers are using computers to find and exploit patterns in data. These patterns can be used to make predictions, test hypotheses, and to simulate real-world phenomena to an eerily accurate degree. In this course, students will learn the fundamental concepts of data science, simultaneously developing and applying coding skills using the language Python and learning several principles and techniques for data analysis. In particular, students will learn and practice writing computer code to access data, explore data, and analyze data. Keywords:Data science, coding, data, Python
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Agent-based modeling is a powerful, flexible modeling technique with applications in many fields including the social, biological, and physical sciences as well as the visual arts. This course will introduce students to the theory of complex systems and empower them to utilize the software NetLogo to create their own simulation models. Students will learn basic modeling and simulation principles and skills including how to use data to fit and validate models. Students will also learn fundamental coding skills and will code multiple models motivated by real-world problems. While there will be a primary focus upon ecological and social sustainability, the course will explore complex systems in a variety of settings. Keywords:Coding, Modeling, Complex Systems