is an assistant professor in the Pattern Recognition and Machine Intelligence group in the Department of Electrical and Computer Engineering at the University of À¶Ý®ÊÓƵ. He received his PhD and MSc in computer science from the University of British Columbia working in the , and a BA in computer science from York University in Toronto. He did a postdoc at Oregon State University working with . Mark’s research focuses on algorithms, tools and theory at the intersection of machine learning, optimization and probabilistic modelling. In particular he is interested in the challenges for traditional machine learning and optimization algorithms that arise in domains with spatial dynamics and very large amounts of data. He often works in collaboration with researchers in other fields such as sustainable forest management, ecology and resource economics. He is an active part of building the interdisciplinary research community and blogs on this topic as well as democratic reform and the impact of Artificial Intelligence [AI] technology on society.