Hi! I am a PhD Candidate in Psychology here at UW with a minor in quantitative science. My general research interest is in bias in person perception, with my dissertation focusing on the intersectionality between multiple forms of discrimination and bias (e.g. age, gender and race).

Originally from Southern California I relocated to Seattle in the Fall of 2014 to start a PhD program in Sociology at the University of Washington. My current research focuses on urban environmental inequality and its relationship to racial/ethnic and economic stratification. I’m pursuing several projects looking at the relationships between residential mobility/stratification and air pollution.

My name is Sean Wang, and I’m very much not a data scientist. In real life, I am a PhD candidate in geography at Syracuse University. My dissertation research looks at the politics of immigration and birthright citizenship policies, via a comparative ethnography between local responses to Chinese birth tourism in Hong Kong and southern California, respectively. (It’s okay- my real life is not very interesting.) In my past life, I was a demographer trained right here at UW, so I’m very excited to be back to my old stomping grounds this summer!

My name is Rachael, and I am one of four fellows working on investigating alternatives to census data as a means to estimate the spatial distribution of poverty on the Crowdsensing Census project in the Data Science for Social Good program at UW.

I am a 2nd-year doctoral student at the University of Maryland, College Park studying information science (a.k.a., Maryland’s iSchool). Specifically, I am interested in understanding how socio-technical factors affect various kinds of communities and organizations, and in designing social computing systems to solve community problems.

I am an undergraduate student at the University of Washington in the Applied and Computational Math Sciences Program with a focus in Discrete Math and Algorithms. I am most interested in data-driven modelling, data visualization, and machine learning.

Hello! My name is Mike Munsell and I am a PhD candidate in Economics at Brandeis University (Boston, MA). I am a Michigan native and completed my undergraduate degree at the University of Michigan (Go Blue!). My research interests include the use of machine learning techniques to improve the accuracy of macroeconomic forecasts.

I am a PhD student in Human-Centered Design and Engineering at the University of Washington. My primary my research concentration is visual analytics, and I am also involved with ethnographic work at the eScience Institute.

I am a master’s student in library and information science at UW where I focus on data management, curation, and visualization. My undergraduate background is in environmental science, and before starting the MLIS program I worked as a data manager on research projects dealing with lake ecology and climate change. I’m excited to approach research with a more explicitly human-centered perspective this summer.

I am a graduate student in Landscape Architecture at the University of Washington where I also work for Urban@UW.

I am a graduate student in Information Systems at Boston University, with a concentration in Data Analytics. I received my Bachelor's from Emory University in Atlanta, GA. After graduating I worked as an IT Consultant with Oracle for their knowledge management and enterprise search software.

This summer, I look forward to learning more about the intersection of Social Sciences and Data Science. I also look forward to further developing my background in Text Mining and Machine Learning, which our project, Unsafe Foods, focuses on. I also hope to become more proficient in Python. As far as this program specifically has to offer, I am very excited to spend ten weeks in the beautiful city of Seattle, visit Olympic National Park, and spend my time in the pleasant confines of the UW eScience Institute!

I’m a PhD Candidate in Political Science here at UW, where I also work as a consultant at CSSCR (the Center for Social Science Computation and Research). My dissertation uses a combination of qualitative fieldwork and quantitative analysis to evaluate the impact of local participatory budgeting reforms on communities’ wider practices of civic engagement.

I am a graduate student of Data Science at Columbia University. I previously worked for 3 years at Sinnia (link), a startup dedicated to social network analysis, as a Data Scientist on data visualization, text mining, machine learning and statistical modeling. I was born and raised in Mexico City, where I received my Bachelor’s degree in Applied Mathematics at ITAM (Mexico Autonomous Institute of Technology). During my undergraduate studies I became passionate about statistics, mathematics and information technology, which led me to the field of Data Science. Growing up, I realized that the socioeconomic inequality prevalent in my home country has yet to be adequately addressed. I feel that as an advanced Data scientist and statistician, I can achieve more for my country and its inhabitants by applying what I learn in this fellowship back home for the betterment of the Mexican community.