Many areas of human endeavour require decision making about complex systems, where there is: uncertainty about the causal process driving the system; limited and possibly inaccurate information about the current state of the system; and uncertainty about the effects of actions or interventions.
Bayesian networks have become a state-of-the-art technology to support decision-making under uncertainty. These models can combine data, evidence, opinion and guesstimates to help decisions makers combine probabilities and take into account costs and benefits.
In this public lecture Professor Ann Nicholson, Deputy Dean of the Faculty of Information Technology at Monash University, will demonstrate Bayesian networks broad applicability across a range of examples, and describe some of the challenges in building these models and having them adopted by decision makers.
Networking, drinks and nibbles from 6pm, with Professor Ann Nicholson's presentation to begin at 7pm.
If you would like to attend this talk please RSVP online here.
Professor Ann Nicholson is the Deputy Dean in the Faculty of Information Technology at Monash University.
After completing her BSc (Hons) and MSc in Computer Science at the University of Melbourne, she was awarded a Rhodes scholarship to Oxford, where she did her doctorate in the Robotics Research Group.
After completing a post-doc at Brown University, she returned to Australia to take up a lecturing position at Monash.
Professor Nicholson researches in the broad areas of Artificial Intelligence and machine learning. She is a leading international researcher in Bayesian networks, now the dominant technology for probabilistic causal modelling in intelligent systems. She has applied Bayesian Network technology to problem-solving in many domains including meteorology, epidemiology, medicine, education and environmental science. Examples include the use of BNs in biosecurity risk assessment, predicting the impact of conservation actions on threats