Rinita Roy

Rinita Roy is a researcher at the Technical University of Munich (Technische Universität München, TUM), specializing in areas such as data analytics, algorithms, and machine learning. Her academic work has garnered significant attention, with over 110 citations on Google Scholar, indicating her contributions to the field are well recognized.

Research Contributions

Roy's research includes various topics and publications, notably:

• Mining trips from location-based social networks: This study focuses on clustering travelers and destinations, published in Information Technology & Tourism in 2020.
• Optimization of stego images: In this work, she explored genetic algorithms for image steganography, published in Procedia Computer Science in 2015.
• Characterization of traveler types: This research utilized check-in data from social networks to analyze different traveler profiles, featured in a 2019 publication.

Academic Background

Rinita Roy's work at TUM emphasizes practical applications of machine learning and data analysis, particularly in tourism and travel-related technologies. Her research has implications for enhancing user experiences through personalized recommendations based on data-driven insights.

Overall, Rinita Roy is an emerging figure in her field, contributing valuable research that bridges technology and user experience in tourism.