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Kaylea Champion, Chin-Wei Chen, & Nathan Welch + Graduating Student Awards


Presenting certificates of completion to the 2024 CSSS Track students and research presentations by 3 students. 

Kaylea Champion 
Kaylea Champion is a PhD Candidate in Communication, where she studies how people work together to build and maintain amazing public goods like knowledge and software -- including what ends up neglected and who is excluded. She has a Master's degree in Computer Science from the University of Chicago and a background in education and information technology. 

Her dissertation develops evidence that significant risks to our shared digital infrastructure -- communication systems, servers, and applications -- can be identified by examining the sociotechnical conditions of the organizations which produce that infrastructure. 

Chin-Wei Chen
Chin-Wei is a Fulbright Scholar, Ph.D. student in Urban Design and Planning, and an affiliated researcher in the Urban Infrastructure Lab at UW. As a professionally trained planner, Chin-Wei specializes in climate adaptation, social equity, resilience, and energy transition within infrastructure planning, with a particular focus on long-term climate policies and interdisciplinary cooperation to effectively address environmental challenges.

Adept at both quantitative and qualitative methods, Chin-Wei analyzes the opportunities and challenges of climate actions across multiple cities, including projects understanding the diffusion of climate justice considerations in city policies, analyzing the impact of public climate investments on electric vehicle adoption, addressing clean energy accessibility for marginalized communities, and integrating social equity into capital planning processes.

Chin-Wei has earned a Master’s degree in urban design and planning from the University of Manchester and a Bachelor's degree in Real Estate and Built Environment from National Taipei University.

Nathan Welch
Nathan Welch is a PhD Candidate in the Department of Statistics. His research focuses on probabilistic forecasting methods for human migration. He has a Master’s degree in Mathematics and Statistics from Georgetown University and Bachelor’s degree in Mathematics from the University of Alabama at Birmingham. 

He developed a novel Bayesian hierarchical model of international bilateral migration flows for all countries, decreasing forecast error by 61% compared to a leading model of international migration. He also developed an approach that accounts for population age structure in long-term international migration forecasts, leading to more precise forecasts of global net migration. His final dissertation project develops a Bayesian discrete choice model framework to resolve address imputation methodological challenges identified in the National Academies of Sciences’ report on the 2020 Decennial Census.  

As he completes his final PhD requirements this year, Nathan is applying his dissertation research as a Lead Data Scientist at a federally funded research and development center (FFRDC).