What computational principles explain the success of human intelligence? I will describe recent work that combines together the unbounded flexibility of mathematical logic with the robustness of statistical inference. This combination brings us several steps closer to understanding human intelligence -- and to the tools for true intelligence engineering. Noah D. Goodman is a research scientist in the Department of Brain and Cognitive Sciences at MIT, and a member of the Computer Science and Artificial Intelligence Laboratory. He studies the computational basis of human thought, merging behavioral experiments with formal methods from statistics and logic. He received his Ph.D. in mathematics from the University of Texas at Austin. After a brief stint as a Chicago real estate developer, he joined the Computational Cognitive Science group at MIT. Goodman has published more than thirty publications in psychology, cognitive science, artificial intelligence, and mathematics. Several of these papers have won awards.