AI in practice: Model Distillation

Mark Carman is an Associate Professor at the Politecnico di Milano, where he teaches courses in Data Science and Artificial Intelligence. Prof. Carman's research interests lie in the areas of information retrieval and machine learning. His specific areas of expertise include rank learning techniques for Web search engines, quality control techniques for crowdsourcing, statistical modelling of text for sentiment and sarcasm detection, models of user expertise online, topic models for personalising search results, product recommendation, clustering & anomaly detection techniques, text extraction from images, and digital forensics. Moreover, Prof. Carman has experience working with and/or extending a large variety of machine learning techniques including Bayesian networks, graphical and topic modelling, non-parametric models and Bayesian statistics, inductive logic programming, regression tree ensembles, large scale optimisation/learning problems, time series models, self-exciting processes, bandit algorithms and various areas of deep learning (applied to both images and text). Mark Carman graduated with a Bachelor of Electrical and Electronic Engineering and Arts (with First Class Honours) from the University of Adelaide in 2000. He spent a year working at Telstra Research in Sydney, before moving to Trento to work at the Fondazione Bruno Kessler. He received a PhD in Computer Science from the University of Trento in 2006. During and immediately after his Phd he spent 2 years at the Information Sciences Institute of the University of Southern California. In 2007 he moved to Lugano (Switzerland) where he worked did a postdoc at the Università della Svizzera Italiana. In 2010, he moved to Melbourne (Australia) to join the Faculty of IT at Monash University, first as as a lecturer and later as a senior lecturer. After eight years in Melbourne he moved to Milan to join DEIB as an Associate Professor.