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Our Faculty

The team of faculty for the online Master of Science in Applied Statistics is led by Thomas Ilvento, Professor and Program Director of MS in Applied Statistics. Professional statisticians working at leading organizations developed courses specifically for the University of Delaware’s online master’s degree program in applied statistics, which also includes courses developed by the distinguished full-time faculty members who teach our on-campus students. All of the courses for the online program are managed by master’s degree level statisticians who are APEC faculty members.

“The online learning experience at UD was excellent. Professors were very responsive to questions and concerns throughout each of my courses.”
Michelle Wilde, MS in Applied Statistics Graduate

Photo of Thomas Ilvento

Thomas Ilvento, Ph.D.

Professor and Director of MS in Applied Statistics
Department of Applied Economics and Statistics
Office: 302-831-6773

Thomas Ilvento specializes in collaborative needs assessment projects, in which he involves industry professionals in the design and implementation of surveys, focus groups, and other methods. His experience also includes public policy, business retention, community needs assessment, and collaborative problem solving.

Ilvento is trained in research methodology, applied statistics, demography, facilitation, mediation, and collaborative problem solving. He teaches graduate and undergraduate courses in applied statistics and has taught online class for more than 15 years. He also runs the StatLab, a statistical consulting opportunity for students, faculty, and outside companies and organizations.

Ilvento has co-authored numerous published studies and is the author of the text, 2013 Statistics, Plain and Simple. He earned his Ph.D. in rural sociology and his B.S. degree in Community Development, both from Pennsylvania State University. He holds an M.S. in Resource Economics/Community Development from the University of New Hampshire. Prior to joining the University of Delaware, he was an Associate Professor at the University of Kentucky.

Photo of Patrick DeFeo

Patrick DeFeo, Ph.D.

Adjunct Instructor
Department of Applied Economics
Course Developer
Online M.S. in Applied Statistics

Patrick DeFeo is an Adjunct Instructor for the Department of Applied Economics and Statistics and a Course Developer for the department’s Online M.S. in Applied Statistics degree program.

As the Principal Consultant Statistician for the DuPont Company, DeFeo has provided statistical leadership working with multidisciplinary teams in product development and process improvement. He has lead project teams, designed studies, and used advanced statistical analyses to provide practical guidance for complex business projects.

During his 29 years at DuPont, DeFeo has taught training in design of experiments, data analysis, and statistical process control. He has also taught Six Sigma training for Black Belts and Master Black Belts at the organization and is a DuPont certified Master Black Belt.

DeFeo holds a Ph.D. and M.S. in Statistics, both from Virginia Tech, and a B.S. in Mathematics from Montclair State College.

Photo of Steven P. Bailey

Steven P. Bailey, Ph.D., CSSBB, CMBB

Course Developer
Online M.S. in Applied Statistics

Steven P. Bailey was with DuPont’s corporate Applied Statistics Group for over 36 years until his retirement as a principal consultant in 2016. During his last 16 years with DuPont, Bailey led DuPont’s corporate Six Sigma Master Black Belt Network. A past president and chairman of the board of the American Society for Quality (ASQ), he is certified as a Six Sigma Black Belt and Master Black Belt by both DuPont and ASQ.

Bailey, who served as an adjunct faculty member in UD’s Department of Applied Economics and Statistics, has been an instructor for the Predictive Analytics and Data Mining Certificate program since 2012. He also provides statistics and Six Sigma training and consulting services for a variety of businesses. He earned his B.S., M.S. and doctorate in statistics at the University of Wisconsin in 1974, 1975 and 1979, respectively.

Photo of Chunbo Fan

Chunbo Fan, Ph.D.

Assistant Professor and Course Developer
Online M.S. Applied Statistics

Chunbo Fan’s focus is on promoting students’ academic success which extends to their professional achievements. She emphasizes on combining real-world practices to theoretical training in statistics, and encourage students to apply critical thinking in their daily situations.

Before joining UD, Fan was an Associate Director at Bayer Pharmaceutical, and a manager of Quantitative Commercial Insight at Astrazeneca Pharmaceutical. She has more than 11 years of experience in the industry, specializing in commercial analytics, marketing mix modeling, and commercial experiment and pilot programs.

Chunbo earned her Ph.D. and her M.S. from the University of Delaware, and she holds a B.S. from the Central University of Finance and Economics (China).

Photo of Hemei Liu

Hemei Liu, M.S.

Course Developer
Online M.S. Applied Statistics

Hemei Liu is a Supervisory Specialist in the Federal Reserve Bank of Philadelphia, and a Course Developer for the Online M.S. in Applied Statistics Degree Program. Prior to joining the Federal Reserve Bank, she was a quantitative operation manager at the Bank of American.

She has nineteen year of banking experience with proven modeling skills, in-depth knowledge on portfolio profit growth through credit line optimization, subject-expert on data quality monitor, model performance tracking, and experimental design.

Her modeling skills include binary logistic regression, multinomial logit analysis, logit analysis for longitudinal data, discrete time survival analysis, multivariate linear regression, time series model, valuation-framework profit model, optimization, machine learning, cluster analysis, multi-level experimental design, model performance evaluation, variable screening, model validation, data quality monitoring, and model examination.

Her honor and achievements include a US patent for the novel methodology of monitoring model score migration, generating incremental $60mm profit per year from her credit line increase model, generating $6.6mm expense saving per year from her collection model, and generating $22mm capital saving per year from her reward point breakage model.

Hemei holds a M.S. in Statistic from the University of Delaware, a M.A. in Energy and Environmental Policy from the University of Delaware, and a B.S. in Mathematical Statistics from the NanKai University.

Joseph Scocas, M.S.

Course Developer
Online M.S. Applied Statistics

Joseph Scocas is an Adjunct Instructor for the Department of Applied Economics and a Course Developer for the Online M.S. in Applied Statistics degree program.

He has worked at DuPont since 2007 and, in his current role as Statistician/Research Investigator with the Crop Protection division, his responsibilities include statistical simulations; analysis, using generalized linear mixed models; project management; support of discovery; and development and product support. He also has developed Design of Experiments (DoE) training, supervised master-level contractors and mentored graduate-level interns. Scocas previously served as a Statistician/Consulting Statistician at DuPont, working with multiple divisions as a member of DuET’s Applied Statistics Group.

Prior to joining DuPont, Scocas served as a Financial Officer, Mortgage Officer, and Management Analyst for the Delaware State Housing Authority, where he provided financial reports to investors, performed financial and regulatory compliance on loan applications, and provided internal and external statistical support.

He is Six Sigma Green Belt certified and Black Belt trained. Scocas is also an expert in the use of SAS programming including SQL coding, SAS macro language, statistical procedures, and advanced graph programming.

Scocas holds a M.S. in Statistics and a B.B.A. in Operations Management and Supervision, both from the University of Delaware.

Photo of Yihuan Xu

Yihuan Xu, Ph.D.

Course Developer
Online M.S. in Applied Statistics

Yihuan Xu is an associate director in the biometrics department at BeiGene Ltd where she works as a biostatistician to support clinical development of multiple oncology drugs. Prior to joining BeiGene, Xu worked as a biostatistician at Eli Lilly and Company in New Jersey for 10 years, supporting the Cyramza program on multiple phase II/III clinical trials. Before that, Xu was a biostatistician in Thomas Jefferson University Cancer center where she provided statistical support on cancer research across cancer biology to clinical studies.

Xu earned her medical degree from Peking University Health Science Center. She also received her Ph.D. in Statistics from Temple University and her M.S. degrees in Molecular Biology and Statistics from University of Delaware.

Her research interest is in survival analysis in oncology clinical trials, especially in biomarker enrichment study design and non-proportional hazard survival analysis.

Photo of Yan Yuan

Yan Yuan

Assistant Professor
Online M.S. in Applied Statistics

Dr. Yuan is an active teacher and researcher with extensive experience in economics, econometrics and general data analysis. She holds a Ph.D. in Agricultural Economics from Texas A&M University and an M.S. in Food and Resource Economics from the University of Delaware. Dr. Yuan has taught at several universities, including the University of Delaware, Texas Christian University and Southwestern University of Finance and Economics in China.

Dr. Yuan’s teaching experience includes a diverse range of courses in economics and research methods. For the M.S. in Applied Statistics, Dr. Yuan teaches STAT619 Time Series; STAT613 Applied Multivariate Analysis; STAT674 SAS; and the math review class. In addition, Dr. Yuan is developing a new class in applied econometrics, to be offered in Fall 2023.

Dr. Yuan’s research interests include financial literacy, credit accessibility and small business dynamics in China. She has published papers in China Economic Review, Pacific-Basin Finance Journal and Journal of Family and Economic Issues. She has received the 2015 Best Paper Award from China Economic Review and honorable mention for the Dr. Werner Jackstädt Best Paper Award for Chinese Economic and Business Studies in 2014. Dr. Yuan builds economic data into many of her courses, including exploring some of the issues and problems inherent to data that reflects prices, demand and supply.

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