Visionary scientist, computer scientist and mathematician with extensive experience in applying AI, decision analysis, and statistics to real-world problems; for example, in Health, in Defense & Security, and for the Environment. Of particular interest is "Broad AI", which goes beyond the confines of "Narrow AI".
Broad AI features AI systems that use and integrate multi-modal data streams, learn more efficiently and flexibly, and traverse multiple tasks and domains. This includes:
I have been involved with AI for over 30 years and am regarded as one of the leaders in the field.
My knowledge and experience includes all the current machine-learning techniques as well as formal AI logics such as Bayesian inference and Dempster-Shafer theory. For all these areas, I have both in-depth theoretical knowledge as well as experience of the realities of their implementation in the real world.
In addition to my research papers, I have produced two books on the use of AI for medicine:
I have given many invited talks on AI, one of which is “Bayesian Networks and their Place within Big Data” at Chalmers University, Sweden, in March 2017: