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About

Julia Szeles is a researcher at the intersection of assistive robotics, intelligent control systems, and human-centered computing for aging populations. Her work focuses on developing practical, sensor-driven technologies that enhance the independence and safety of elderly individuals. Szeles’s most impactful contribution is a weather forecast support system integrated into a robot partner, which uses fuzzy logic to analyze real-time data—such as temperature, wind speed, and weather conditions—to provide personalized daily recommendations for seniors. This paper has garnered 7 citations, reflecting its relevance to ambient assisted living. She has also advanced location monitoring applications for smartphones, employing intuitive interface designs to help caregivers track elderly users, a work cited 6 times. In control engineering, Szeles optimized a Proportional-Summation-Difference controller for a line-tracing robot using a Bacterial Memetic Algorithm, achieving 4 citations. Her research uniquely bridges robotic autonomy with user-friendly, context-aware support, demonstrating a commitment to translating complex algorithms into tangible aids for vulnerable populations. Szeles’s work is a valuable resource for students and researchers exploring socially assistive robotics, fuzzy systems, and inclusive technology design.