Jey Han Lau

Biography

Jey Han obtained his PhD in Computer Science from the University Melbourne in 2013, with a PhD thesis on LDA topic models. Before joining IBM, he was a research associate in King's College London, working on a project with to develop stochastic models that represent the syntactic knowledge that all native speakers share. Jey Han's general interest is in unsupervised learning, an area which develops algorithms to discover structure in languages with minimal or zero supervision. He has worked with applying these algorithms to variety of natural language problems, from discovering word meanings to detecting novel events in social media to predicting the well-formedness of a natural language sentence. Jey Han obtained his PhD in Computer Science from the University Melbourne in 2013, with a PhD thesis on LDA topic models. Before joining IBM, he was a research associate in King's College London, working on a project with to develop stochastic models that represent the syntactic knowledge that all native speakers share. Jey Han's general interest is in unsupervised learning, an area which develops algorithms to discover structure in languages with minimal or zero supervision. He has worked with applying these algorithms to variety of natural language problems, from discovering word meanings to detecting novel events in social media to predicting the well-formedness of a natural language sentence.

Research Interest

Unsupervised Learning, Deep Learning, Language Models, Bayesian Graphical Models, Cognition and Linguistic Knowledge