Interests and expertise that span across a number of disciplines including: knowledge representation, reasoning about actions, natural language processing, probabilistic logics, non-montonic logics, argumentation, Bayesian reasoning, statistical machine learning, data science and crowdsourcing. Our overarching research objective is to develop methodologies, algorithms and paradigms that build bridges between logic-based AI and statistical machine learning approaches, as well as finding practical applications in robust real-world applications.