The field of pattern analysis and machine learning encompasses theories, methods, operations, and system designs focused on the perception, recognition, and analysis of patterns in various forms, such as visual, textual, numeric, or multimedia. It also involves creating systems, machines, and programs that demonstrate adaptable and intelligent behavior. This area includes several subfields within artificial intelligence and machine learning, including sensor management and perception, affective computing, activity recognition, data mining and knowledge discovery, cognitive robotics, cooperative intelligent systems, biometrics, video and image analysis, natural speech recognition, human-machine interaction, and their applications. These subfields form the foundation of a wide range of applications, such as intelligent transportation systems, service robotics, speech transcription, document classification and clustering, computer vision, emotion recognition, commodity prediction, and intelligent power engineering.
Members of the AI and ML field are highly esteemed researchers, known for their significant contributions, which include over 50 patents and the establishment of five spin-off companies. AI and ML researchers organize numerous international conferences and workshops each year in their domain. The field attracts some of the world’s top researchers and graduate students. Upon graduation, AI and ML graduates are in high demand by both academic institutions and industry. Research and training are conducted using the latest software and hardware available, with courses in this area being rare at other institutions. Graduate students also contribute substantially to intellectual property, often resulting in patents and software products.
