Novi Quadrianto

Novi received his PhD in Computer Science from the Australian National University (ANU), Canberra, Australia in 2012. He earned BEng degree in Electrical and Electronics Engineering at Nanyang Technological University (NTU), Singapore. He is now a Newton Fellow of the Royal Society at Department of Engineering of University of Cambridge, and a Junior Fellow of the Wolfson College.

His research focuses on addressing challenges for Internet applications in the context of machine learning. His contributions include streaming algorithms for learning to utilise massive un-labeled Internet data, and for tiering search engine indices that can process billions of webpages in seconds. He has also contributed in non-standard learning settings such as learning from only label proportions, learning from several related tasks with distinct label sets, and inferring bipartite matching with un-observed edge potentials. At the moment, he focuses on nonparametric Bayesian models which allow flexible modelling of complex Internet data. For more information, please refer to:

Selected Publications