Yan Li is an assistant professor in Claremont Graduate University’s Center for Information Systems & Technology (CISAT). Her research focuses on such data and knowledge management areas as data mining, business intelligence, and data warehousing as well as on semantic technologies with an emphasis on exploring the synergies between information systems and advanced data analytics. Her other research stream focuses on developing Information & Communication Technology (ICT) solutions for underserved populations in low-resource areas and improving social inclusion in health care.
Li received both an MS and PhD from Virginia Commonwealth University. Prior to joining CISAT, Li was a data scientist in industry, giving her hands-on experience in advanced analytics, machine learning, and big data platforms.
Li recently received two $20,000 Microsoft Azure Research Awards. The first is to design a data pipeline framework for social media analysis. The second is for a Continuing Medical Education capacity building for developing countries. She has published numerous journal articles and book chapters, and she has delivered many conference presentations in the fields of data mining and other forms of data analysis. She investigates and learns new and advanced methods, techniques, and tools for big data analytics, text mining, ETL, business intelligence and visual analytics, and multiple-criteria decision analysis.
Driven by her intellectual curiosity for data and emergent information technologies and by her passion for designing and building, Li has oriented her career in a direction that integrates research, teaching, and practice in the realm of information science. Attracted by CISAT’s distinctive design- and practice-based approaches to solve important social and business problems, Li seeks to expand her career at CGU as an assistant professor of data science.
Co-authored with Thomas, M., and Oliveira, T. (2017). “Nuances of Development Contexts for ICT4D Research in Least Developed Countries: An Empirical Investigation in Haiti.” Telematics and Informatics.
Co-authored with Vo, A, Randhawa, M, Fick G. (2017). “Designing utilization-based spatial healthcare accessibility decision support systems: A case of a regional health plan.” Decision Support Systems.
Co-authored with Thomas, M. A., Osei-Bryson, K.-M. and Levy, J. (2016). “Problem Formulation in Knowledge Discovery via Data Analytics (KDDA) for Environmental Risk Management.” International Journal of Environmental Research and Public Health, 13(12), 1245.
Co-authored with Thomas, M. A., & Osei-Bryson, K.-M. (2016). “A Snail Shell Process Model for Knowledge Discovery via Data Analytics.” Decision Support Systems, 91, 1-12.
Co-authored with Manoj A. Thomas and Kweku-Muata Osei-Bryson. “Ontology-based data mining model management for self-service knowledge discovery.” Information Systems Frontiers (2016): 1–19.
Co-authored with Roland Weistroffer. “Multiple Criteria Decision Analysis Software.” In Multiple Criteria Decision Analysis: State of the Art Survey, edited by José Figueira, et al. 1301–41. New York: Springer-Verlag, 2016.
Co-authored with Manoj Thomas and Kweku-Muata Osei-Bryson. “Using association rules mining to facilitate qualitative data analysis in theory building.” In Advances in research methods for information systems research, edited by Kweku-Muata Osei-Bryson and Ojelanki Ngwenyama, 79–92. New York: Springer, 2014.
Databases & Big Data
Knowledge Discovery & Data Mining
Data Science Practicum