Avi is a Ph.D. Candidate in Complex Systems and Data Science at the University of Vermont, co-advised by Juniper Lovato. His research sits at the intersection of machine learning, natural language processing, and computational social science. Broadly, he is interested in understanding how LLMs think and its socio-technical impact in higher education.
Callandra Moore is a PhD student in Complex Systems and Data Science at the University of Vermont. She is a long-time social justice activist whose research interests are primarily in the use of quantitative and computational methods to advance research on human rights. She has a Bachelor of Applied Science in engineering physics and political science and a Master of Public Health in epidemiology, both from the University of Toronto.
Chris Donovan is a PhD student in Complex Systems and Data Science at the University of Vermont and serves as a Food Systems Data Scientist at the Food Systems Research Institute. His work involves food system sustainability research, on-farm research networks, and cultivating FAIR data, while his research pursuits include participatory food systems modeling and reproducible analytical workflows. Chris has a MS in Community Development and Applied Economics from UVM and a BS in Environmental Studies with an emphasis in Conservation Biology from Prescott College.
Jeremy Elliott is a PhD student in Complex Systems and Data Science at the University of Vermont, co-advised by Trisha Shrum in the department of Community Development and Applied Economics. His current research examines how story structure motivates pro-environmental behavior within a highly effective climate intervention. More broadly, he’s interested in using data science to understand the drivers of pro-social behavior, and how to communicate data effectively. He holds a B.S. in Physics with Honors from UVM.
Luc Cohen-Wanis is pursuing a PhD in Complex Systems and Data Science at the University of Vermont, where he explores how data science and statistical modeling can drive meaningful social impact. His current research interests center on applied statistics and quantitative social science, including collaborative work with Professor Sam Zhang to uncover patterns in faculty hiring and attrition and other interdisciplinary topics. He has a MS in Statistics from the University of Vermont and BS in Mathematics from University of California, Irvine.
Rae Tiffen is pursuing a Certificate of Graduate Study in Complex Systems and Data Science at the University of Vermont. They are interested in the development and application of causal inference methods, and have recently been working on understanding shifts in the academic labor market to political changes. They have a Bachelor of Science in Economics and Bachelor of Arts in Russian & East European Studies, both from the University of Vermont.
Sam Zhang is the director of the Science and Humanity Lab, an Assistant Professor in the Department of Mathematics and Statistics at the University of Vermont, and core faculty in the Vermont Complex Systems Institute. With his collaborators, he develops and applies methods drawing on mathematics, network science, and data science to examine how institutions shape scientific careers, how biases and hierarchies propagate through systems, and how quantitative approaches can inform humanitarian questions of rights, justice, and policy. He received his PhD in Applied Mathematics at the University of Colorado, Boulder.
Samantha Magid is pursuing an MS in Complex Systems and Data Science at the Vermont Complex Systems Institute, where she studies mathematical and probabilistic approaches to interdisciplinary complex systems. Her work with Sam Zhang centers around stochastic approaches to understanding scientific productivity. She is interested in metascience, sequential systems, and causal inference. She holds a B.S. in Data Science and Environmental Science from Boston University.
Short description of portfolio item number 1
Short description of portfolio item number 2
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1).
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Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2).
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Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3).
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Published in GitHub Journal of Bugs, 2024
This paper is about fixing template issue #693.
Recommended citation: Your Name, You. (2024). "Paper Title Number 3." GitHub Journal of Bugs. 1(3).
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Published in GitHub Journal of Bugs, 2024
This paper is about a famous math equation, \(E=mc^2\)
Recommended citation: Your Name, You. (2024). "Paper Title Number 3." GitHub Journal of Bugs. 1(3).
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Published:
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Published:
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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