We are constantly exploring new research questions, projects and collaborators. With direct access to librarians, collections and data sets, the Unit for Data Science and Analytics, headquartered in Hayden Library on ASU's Tempe campus, is uniquely equipped to connect people, ideas and resources university-wide.
Come to our open sessions. Our team regularly hosts work-ins, meet and greets, and other events that are open to ASU students, faculty, staff and the surrounding community.
Collaborate with our team. Show us what you’re working on or just come explore. If you are new to this domain, that’s even better. Discover how your expertise and interests fit in.
Consult on a specific issue. We can connect you with people, resources, and more through our networks across ASU and within ASU Library.
Faculty, staff and students interested in an ongoing project, new collaboration or learning more may contact datascience@asu.edu.
Who we are
Kerri Rittschof
Director, Data Science and Analytics
Kerri’s expertise is in developing, implementing and maintaining programs; managing teams and activities; conducting research and writing reports. Prior to joining the library, she was an ASU Program Manager, leading a team of researchers to evaluate evidence-based programs and collaborate with child social welfare agencies. She holds a Ph.D. in Organizational Psychology.
Namig Abbasov, PhD
Digital Humanities Analyst, Data Science and Analytics
Namig is responsible for designing, creating, and deploying various statistical and computational tools, including modern applications of data science to digital humanities and social sciences, to assist the ASU community. He is interested in machine learning and ensemble forecasting techniques, viewing them as transformative tools that can enhance predictive modeling across the intersecting fields of social sciences and digital humanities. He is dedicated to continuing professional growth with training in text analysis, large-scale data, and network analysis to resolve advanced research problems. He received a Ph.D. in Political Science from the School of Politics and Global Studies at Arizona State University.
Michael Simeone
Researcher and lab fellow
Michael is a researcher interested in multidisciplinary data science. He currently serves as a researcher with the Global Futures Lab, School of Complex Adaptive Systems. He served as the founding director of the Data Science and Analytics for ASU Libraries bring a wealth of data science knowledge and experience to students, faculty and staff. Further, Michael was the founding director of ASU’s Nexus Lab for Digital Humanities and Transdisciplinary Informatics, and the Associate Director of the Institute for Computing in Humanities, Arts, and Social Science at the National Center for Supercomputing Applications. He earned his PhD in English Language and Literature/Letters from the University of Illinois at Urbana-Champaign.
Shawn Walker
Assistant Professor and lab fellow
Shawn is an Assistant Professor of Critical Data Studies in the School of Social and Behavioral Sciences on ASU’s West Valley campus. His research focuses on mis and disinformation and online resistance circulating in social media during social movements, protests, and elections as well as the related challenges of collecting, analyzing, and preserving data from social media platforms. He received his PhD in Information Science from the University of Washington Information School and is a founding member of the Datacification Lab.
Website: https://shawnw.io, @walkeroh
Joffa M. Applegate
Assistant Research Professor
Joffa M. Applegate is an Assistant Research Professor at Arizona State University, and a member of the Complex Systems Research Group, Policy Informatics @ The Decision Theatre and The Global Climate Forum. She holds a master’s degree in Physics and a doctorate in Applied Mathematics for Life and Social Sciences with a concentration in Complex Adaptive Systems Sciences from ASU. Her areas of expertise are complexity economics and complex systems modeling, including multi-agent, dynamical and network modeling.