Sairam Rayaprolu is an Assistant Professor in the Data Science area at IFMR Graduate School  of Business, Krea University. He has worked in decision science and advanced analytics across Travel, Hospitality, Property  & Casualty Insurance, and Retail, spanning more than a decade in the United States,  contributing directly to the analytics lifecycle, from business requirements and measurement  through predictive modeling, AI/ML, and validation. This includes revenue analytics at Walt  Disney Parks and Resorts, auto insurance pricing at Plymouth Rock Assurance, supply chain  forecasting at Blue Yonder, and pricing analytics at United Airlines. He also worked in supply  chain automation at i2 Technologies. 

His experience extends to Banking and Insurance analytics as well, including risk-model data  acquisition as a contractor at Citizens Bank, and machine learning models for Workers’  Compensation insurance risk at Ventiv Technology (now Riskonnect). He has also worked with  generative AI and agentic tools in Facility Maintenance analytics at CBRE. 

He holds a PhD in Statistics from the University of Connecticut and MS degrees in Systems  Engineering and Applied Mathematics from the University of Arizona. His academic path began  with a bachelor’s degree in Chemical Engineering from the Indian Institute of Technology  Bombay. 

Research Interests

Dr. Rayaprolu is a quantitative researcher by training, with broad interests spanning applied  statistical and AI/ML methods for advanced analytics and decision-making under uncertainty,  as well as scientific experimentation. His early research was motivated by statistical hypothesis  testing in brain imaging. More recently, his work has turned to online controlled experiments,  which have transformed product measurement and testing in the technology industry. Digital  experimentation remains an active area of his current research. 

Publications

Rayaprolu, S. and Chi, Z. (2021). “False Discovery Variance Reduction in Large-Scale  Simultaneous Hypothesis Tests.” *Methodology and Computing in Applied Probability*, 23(3),  711–733.

Teaching

Courses at Krea University: 

• Deep Learning and Natural Language
• Processing – Business for e-Commerce
• m-Commerce – AI for Practice