The Evolutionary Computing and Machine Learning (ECML) group at RMIT University studies and develops nature-inspired computational models and algorithms, especially in the areas of evolutionary computation and machine learning and applies them to real-world problems. The group takes an inter-disciplinary approach drawing its inspirations from mathematical programming, meta-heuristics, and operations research. Its current research areas include: large-scale optimization, reinforcement learning, computational intelligence techniques for games, deep learning, multiobjective optimization, data mining and analytics, computer vision, time series analysis, evolutionary art, journey planning, social network analysis, itinerary recommendation, vehicle routing, and swarm intelligence.

Staff: Vic Ciesielski, Xiaodong Li, Andy Song, Fabio Zambetta, Xiaojun Chang, Jeffrey Chan, Timothy Wiley, Vural Aksakalli, Du Yong Kim, Yuan Sun, Haytham Fayek, Minyi Li, Huong Ha, and Li Chik.

News: "The Australian" has just published a special report naming our ECML group at RMIT as the "lead institution" in the area of Evolutionary Computation in Australia. See page 15 of the report here.

News: A news article by EMS reporting about our ARC Linkage Grant project: "Machine learning techniques for fuel loss detection at service statation".