Judea Pearl

Made probabilistic reasoning tractable through Bayesian networks, then formalized causality.

Biography

An Israeli-American computer scientist who introduced Bayesian networks, a graphical representation in which conditional independence is read off the structure of a graph. He subsequently developed a formal calculus for reasoning about causal, as opposed to merely associational, questions.

Key contributions

• Bayesian networks, and efficient algorithms for inference within them.
• The do-calculus and the structural framework for causal inference.
• Substantial early work on heuristic search.

Impact

Bayesian networks made reasoning under uncertainty computationally feasible by exploiting conditional independence, and reintroduced probability to a field that had leaned heavily on logic.