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Maryalice is the Director of Data Analytics at the Center for Innovation in Teaching and Learning and an adjunct assistant professor in the Department of Sociology. She has a Ph.D. in Sociology from Illinois and has been working in statistical consulting at the University since 1999. Her recent research focuses on the economic and health empowerment of women in developing nations. Her other projects relate to program evaluations in academia, including research on the impact of MOOCS (Massive Open Online Courses). She has taught several courses at Illinois, including Introduction to Social Statistics (SOC 280) and Social Research Methods (Soc 380).
Dawn is the Senior Data and Survey Scientist at CITL and the University's official representative to the Inter-university Consortium for Political and Social Research (ICPSR). She has an M.A. in Sociology from Illinois and has worked in the data group (and its former incarnations) in various capacities since 1989. She manages learning analytics data from several sources, helps administers several campus surveys, and provides social science data to members of the university community. She also provides consulting on data management and programming.
Since graduating from Illinois with a B.A. in Economics, Kathleen has taken on the role of Data & Survey Scientist in the Data Analytics unit of CITL. This role focuses on cleaning and coding data for analysis, producing recurring summary statistical reports, and programming online data collection tools. She has a well-working knowledge of SPSS, Python, LaTeX, XML, and their various applications in streamlining data cleaning and reporting. She also has experience in managing and harmonizing datasets across multiple time points (longitudinal and milestone data), multiple survey revisions, and multiple modes of implementation.
Paige is the Postdoctoral Research Associate with CITL's Data Analytics group. She has both an M.S. and Ph.D. in Library and Information Science and an M.A. in Interdisciplinary Studies. At CITL, she works on data collection, preparation, management, and documentation for a variety of projects including online program evaluation and Illinois’ Coursera learning analytics assessment. She is also part of the Illini Success data analysis team shared between CITL and the Career Center.
Aleena Khan is a Ph.D. student in the Department of Political Science at Illinois. Her current academic research focuses on understanding American identity and perceptions of anti-Americanism in the United States. Aleena is also an Associate Policy Researcher at Princeton University’s Bridging Divides Initiative, where she works on tracking threats and harassment to local public officials across the United States. Before coming to Illinois, Aleena worked as. Research Assistant at the Human Services Research Institute in Cambridge, Massachusetts and earned a B.A. in political science from Simmons University. Her expertise lies in survey design and survey experiments using Qualtrics. She also has experience with some Qualitative methods (interviewing and Q-sort), database querying using SQL, creating basic dashboards in Tableau and R Shiny, as well as inferential statistics in R and Stata.
Veronica is a Ph.D. candidate in Civil Engineering and also holds a master's degree in City and Regional Planning. Her research centers around mitigating societal risks and hazards, with a focus on earthquake damage simulation through reliability and network analysis. Her recent work involves optimizing resilience decision-making and proposing statistical methods to validate models using real-world data. Veronica is skilled in SPSS, R, Python, and MATLAB, and has expertise in ArcGIS.
I am a master’s student in Statistics with a concentration in analytics. I have also completed my B.S. in Statistics and Economics with a minor in Computer Science here at Illinois. I specialize in data analytics, time-series forecasting and predictive analysis using machine learning techniques as well as developing interactive dashboards using R Shiny and Python Plotly for data visualization. In addition to R and Python, I am also proficient in C, SAS and SQL.
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