Ross Shachter joined Stanford's faculty directly after receiving his Ph.D. degree. His doctoral dissertation developed a method for purchasing an expert's forecast that encourages accurate revelation of the expert's beliefs as probabilities. Since then his research has focused on the representation, manipulation, and analysis of uncertainty and probabilistic reasoning in decision systems. He developed many of the fundamental methods for analyzing Bayesian belief networks and influence diagrams, and showed how they could be used by people and machines to communicate complex relationships among uncertain quantities, decisions, and objectives. His current research focuses on modeling uncertain processes and decision‐making, including medical policy, meta-analysis, and intelligent systems. He has analyzed cancer screening processes for bladder and breast cancer and vaccination strategies for HIV and Helicobacter pylori.
His research interests include:
Influence diagram knowledge representation and solution;
Intelligent decision systems;
Medical decision analysis;
Decision analysis fundamentals; and
Planning under uncertainty