Rate My Professor Sherri Ni

Dr. Ni has authored numerous publications in these areas, including 'A Bivariate Model for Correlated and Mixed Outcomes: A Case Study on the Simultaneous Prediction of Credit Risk and Profitability of Peer-to-Peer (P2P) Loans' (2025), 'A Survey of Machine Learning Methodologies for Loan Evaluation in Peer-to-Peer (P2P) Lending' (2023), 'Towards Profitability: A Profit-Sensitive Multinomial Logistic Regression for Credit Scoring in Peer-to-Peer Lending' (2022), 'Measuring Customer Similarity and Identifying Cross-Selling Products by Community Detection' (2020), 'Risk Prediction of Peer-to-Peer Lending Market by a LSTM Model with Macroeconomic Factor' (2020), and 'Developing and Improving Risk Models using Machine-learning Based Algorithms' (2019). She has secured funding as principal investigator for projects such as 'Sample and Extrapolation Validation' ($37,500 from Myers and Stauffer LC, 2022-2024, renewed to 2025) and 'Customer Level and Product Level Churn Analysis' ($5,000 from Southern Company, 2023). Under her guidance, student teams have achieved top honors in national competitions like the SAS Student Symposium. Her research has garnered over 400 citations, contributing significantly to advancements in machine learning applications for financial risk and analytics.