Scientists singled out in different kind of talent search

Three local students named semifinalists in Intel’s prestigious

By Christina Lent

The Beaverton Valley Times, Jan 14, 2010

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Meet Yale Fan

Age: 18

Research Project: “Adiabatic quantum algorithms for Boolean satisfiability.”

Explanation: Quantum computers are computers that rely on principles of quantum mechanics to accomplish certain tasks exponentially more efficiently than classical computers. Fan exhibited new numerical and theoretical results on the power of quantum computers for certain classes of NP-complete problems, which are the hardest computational problems with easily verified solutions. This work implies that quantum computers could outperform classical computers for a class of hard problems and gives new insight into the capabilities of prospective technology based on theoretical physics.

Inspiration: “My inspiration came from a line of research I’ve been following through high school, which is the field of quantum computation – a blend of physics, computer science and math. My inspiration for this project came from a summer program through the MIT Research Science Institute. It was a very good experience where I was able to meet grad students and professors who have made big changes in the field.”

Thoughts on being named a semifinalist: “I really appreciate that they recognize work like this. The Intel Science Talent Search is a very nice program because it takes into account your project and your approach to science and encourages high school students to pursue science.”

Future plans: “I plan to study physics. I’m interested in anything quantatated. I would like to be a professor to teach and do research.”

Meet Kevin Ellis

Age: 18

Research Project: “Automatic parallelization through dynamic analysis.”

Explanation: His research is into automatic methods of converting a computer program not designed to use more than one processor into an equivalent program that exploits multiple processors. In doing so, the program can distribute its work and run faster. His method analyzes the program as it executes to reveal parts of the program, which can be distributed, while also showing when distribution programs across multiple processors would increase performance.

Inspiration: “My inspiration was a desire to generalize automatic parallelization. It’s really, really cool because we can automate parallel computing – something usually done by programmers and requires thought. The idea that a computer can do it on its own is exciting because it’s like the computer is thinking.”

Thoughts on being named a semifinalist: “I think it’s really cool. I plan to go to college and this will help. I like that Intel encourages the scientific research of high school students.”

Future plans: “I’m undecided. I’m interested in computer science, math and physics. I would like to figure out what I really want to do. I also find evolutionary biology really interesting.”

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