Bill Gates has referred to computers as "deaf, dumb, blind and clueless." But the "clueless" part may soon be a thing of the past, thanks to computer scientists and their use of Bayesian Networks.

Bayesian Networks are graphical representations of a complex system whereby meticulously gathered data is mapped out in cause-and-effect relationships among key variables, and then encoded with numbers that represent the extent to which one variable is likely to affect another. Programmed into computers, these systems can automatically generate optimal predictions or decisions even when key pieces of information are missing. Today, these networks are used to predict oil and stock prices, control the space shuttle, diagnose disease thereby eliminating exploratory surgery, and make artificial intelligence, well, more intelligent.

Haohai Yu, doctoral candidate in Computer Science and Presidential University Fellow, will be spending the next four years here at Florida State researching Bayesian Networks for computer inference and prediction, with the guidance of his major professor, Robert van Engelen. Haohai explains, "I am interested in designing algorithms that will improve the computational speed and accuracy of Bayesian Networks."

Haohai was born and raised in the manufacturing city of Shenyang, one of China's largest cities with over six million people. He recently worked in Shanghai as a software engineer for the American company, Kodak, and has published articles in several prestigious journals.

He spends his rare, free time watching spur-of-the-moment football games being played across campus. He says, "I am quite impressed by Americans' enthusiasm for the game." Wanting to better understand our culture, he once volunteered to join in. His conclusion? "I am not strong enough."

Maybe not, but then not many people can improve a machine's ability to make decisions faster and more accurately.