š¬ Ehlimana Cogo’s research focus primarily revolves around software engineering and applied artificial intelligence, with an emphasis on developing innovative solutions for software testing, analysis, and optimization. Her work spans various domains, including black-box testing methodologies, machine learning applications, and cause-effect graphing techniques. Through her contributions, she aims to enhance the reliability, efficiency, and security of software systems. Additionally, she explores topics such as warehouse management systems, demand forecasting, and web page layout testing, demonstrating versatility in her research endeavors. With a keen interest in advancing technology, she continually pushes the boundaries of knowledge, making impactful contributions to the field of computer science. š
Publication Top Notes:
Position based visualization of real world warehouse data in a smart warehouse management system
Warehouse demand forecasting based on long short-term memory neural networks
Methods for Automatic Web Page Layout Testing and Analysis: A Review
New graphical software tool for creating cause-effect graph specifications