Principal Data Scientist,
Affiliate Assistant Professor,
UMBC Department of Computer Science and Electrical Engineering
Fei Han, a principal data scientist at The Hilltop Institute, leads and develops predictive analytics using Medicaid, Medicare, MDS, and other data sources. Fei’s specialty is application and theoretical research in statistical learning and machine learning methods. Fei also serves as an affiliate assistant professor doing research in artificial intelligence in the Department of Computer Science and Electrical Engineering at UMBC.
Prior to joining Hilltop, Fei was a statistician for the U.S. Department of Agriculture (USDA), where he developed and modified statistically based national sampling plans for dietary supplement analytical studies. He also developed and implemented a statistical method for quality control of analytical data, designed and administered in-house databases, and used SAS to analyze large data sets. Before that, Fei was a research assistant at Louisiana Tech University. He also has teaching experience as an assistant professor at Huaqiao University (China). Undergraduate courses he taught include probability and mathematical statistics, mathematical modeling, calculus, algebra, operations research, and discrete mathematics.
Fei earned his PhD in computational analysis and modeling, as well as his MS in mathematics and statistics from Louisiana Tech University. He earned an MS in pure mathematics from Huaqiao University (China) and a BS in mathematics and applied mathematics from China University of Geosciences (China).