
Level 1: I use artificial intelligence (AI) to engineer smart systems that learn from experience
Level 2: I take machine learning (ML) algorithms and combine them with declarative programming languages to work on complex data such as networks and dynamic models
Level 3: Combining ML and logic programming to develop explainable AI, we develop novel solutions in applications as diverse as computer chess, online dating and systems biology
I got into engineering because I realised the best way for me to understand complex and interesting systems is to attempt to design and implement them
My research goals are to design and implement computational systems that can learn from experience what they need to know and what they need to do to achieve their design goals
People often don’t understand how difficult it can be to make computers able to do the kind of things they can already "do" in movies and on TV
Engineering can a long and twisty route with lots of intellectual foothills to climb but the sense of achievement from every summit you reach is unbeatable
COMP9417 Machine Learning and Data Mining; BINF2010 Bioinformatics 1; BINF3010 Bioinformatics Methods and Applications; BINF3020 Computational Bioinformatics
Projects are in a wide range of machine learning problems and applications in science and engineering. Examples are: bioinformatics and biomedical informatics; social networks and recommender systems; dynamic systems and control; and music.
Projects are available on a wide range of machine learning problems and applications in science and engineering. Examples are bioinformatics and biomedical informatics, social networks and recommender systems, dynamic systems and control, and music
Smart Services Cooperative Research Centre
Statistics and Modelling Science, University of Strathclyde, UK
BSc (Hons), University of Edinburgh, UK
Dr Michael Bain is a Senior Lecturer with the School of Computer Science and Engineering. His research interests include: