Faculty Profile
Lulu Wang
Assistant Professor of Data Analytics (2024)
Contact Information
Althouse Hall
717-254-8077
Bio
Lulu Wang’s current research interests are in AI model interpretability, especially in finance. Her prior work lies at the intersection of finance, data science, and econometrics, ranging from estimation methods for agent-based models to applying graph neural networks to financial forecasting. She also serves as a statistical consultant in scientific fields such as public health.
Education
- B.Eng., Beijing Technology and Business University, 2008
- M.Sc., University of York, 2013
- Ph.D., City University of New York, 2024
2026-2027 Academic Year
Fall 2026
DATA 300 Statistical & Machine Learning
An introduction to the fundamental concepts and methods for statistical and machine learning. Focus is given on providing both a theoretical foundation and the practical skills needed to apply machine learning to a variety of applications in various disciplines. Topics include supervised methods such as regression and classification, and unsupervised methods such as clustering and dimensionality reduction.Prerequisite: COMP/DATA 200 and MATH 225. Offered every semester.
DATA 400 Data Analytics Capstone
A capstone course that provides students with an opportunity to apply the data analytics knowledge they have acquired to independent research projects. At least one of the projects must be derived from the chosen discipline specific electives. Students will get experience in all aspects of solving real-world problems, including project planning, consideration of legal and ethical issues, collecting and processing data, analyzing and interpreting results, writing reports, and giving presentations.Prerequisites: DATA 300, completion of ECON 298 or concurrent registration in MATH 325, DATA 198/PHIL 258 and the three-course disciplinary sequence. Offered every semester.
Spring 2027
COMP 180 Introduction to Data Science
Cross-listed with DATA 180-01 and MATH 180-01.
COMP 180 Introduction to Data Science
Cross-listed with DATA 180-02 and MATH 180-02.
DATA 180 Introduction to Data Science
Cross-listed with MATH 180-01 and COMP 180-01.
DATA 180 Introduction to Data Science
Cross-listed with MATH 180-02 and COMP 180-02.
MATH 180 Introduction to Data Science
Cross-listed with COMP 180-01 and DATA 180-01.
MATH 180 Introduction to Data Science
Cross-listed with DATA 180-02 and COMP 180-02.
DATA 300 Statistical & Machine Learning
An introduction to the fundamental concepts and methods for statistical and machine learning. Focus is given on providing both a theoretical foundation and the practical skills needed to apply machine learning to a variety of applications in various disciplines. Topics include supervised methods such as regression and classification, and unsupervised methods such as clustering and dimensionality reduction.Prerequisite: COMP/DATA 200 and MATH 225. Offered every semester.