Mayur Khandate
Papers
1
Total Citations
5
H-Index
1
About
Mayur Khandate is an emerging researcher at the intersection of finance and artificial intelligence, with a primary focus on Robotic Process Automation (RPA) and machine learning for financial market applications. His most cited work, "Robotic Process Automation for Stock Selection Process and Price Prediction Model using Machine Learning Techniques" (2022), addresses the growing convergence of automation technologies and stock market participation. In this study, Khandate develops a framework that integrates RPA with machine learning algorithms to streamline stock selection and enhance price prediction accuracy, responding to the surge in retail investor engagement and the rising demand for automation jobs. While his citation count is currently modest at five, the work demonstrates a timely and practical approach to automating complex financial decision-making processes. Khandate's research is notable for bridging two rapidly evolving domains—RPA and quantitative finance—offering a scalable solution that reduces human error and improves efficiency in stock trading. His contributions are particularly relevant for students and practitioners interested in the practical deployment of AI in financial systems, and his work lays a foundation for further exploration into automated, data-driven investment strategies.
Research Focus
Key Achievements
Top Papers
- 1