The QRCC Statistical Consultant team is passionate about statistics and research design and excited about the idea of answering a broad range of advanced statistical questions from across disciplines.
Walter Kaczetow is a doctoral candidate in the Educational Psychology program at the Graduate Center. He is knowledgeable about generalized linear mixed models, psychometrics, item response theory, research design, and penalized regression. He primarily uses Stata, R, and Excel, but has some knowledge of SPSS.
Walter has taught both graduate and undergraduate statistics classes in the psychology and mathematics departments. He has conducted research in academic, non-profit, and government settings. His research has been published in the Journal of Vocational Rehabilitation, Innovative Higher Education, and Multivariate Behavioral Research.
Lulu Wang is a PhD candidate in Economics at the Graduate Center. She also holds an MSc in Mathematical Finance and a BEng in Automation. Her expertise lies in quantitative economics, with a focus on statistical modeling, econometric inference, and advanced estimation methods.
Lulu has extensive knowledge of machine learning models, including graph neural networks, computer vision models, and NLP and XGBoost. She is experienced in numerical methods, utilizing optimization techniques, and solving differential equations. Additionally, she is skilled in handling various types of data, from panel and time series data to large datasets, and is experienced in dimension reduction methods.
Outside of her research, Lulu is a lecturer at Hunter College and brings over 5 years of experience in quantitative trading and asset management.