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Intel Science Talent Search: Changing our Future

Intel, the American billion-dollar company, is known for more than just microprocessors and computer chips. Since 1998, Intel has partnered with the Society for Science and the Public (SSP) to present the Intel Science Talent Search, a program that recognizes high school seniors and their research that could impact our world. The SSP created the Science Talent Search in 1942, making this its 70th year. Each year, 1,800 American high school seniors submit new research, but only 40 finalists are brought to Washington, D.C. to present their projects to judges. The projects range from mathematical theory, medicine, astronomy, engineering, and many more for their work the students are rewarded with scholarships, the grand prize being a $100,000 four-year scholarship. Over the years, hundreds of students have created exciting and innovative research.

Below you’ll find three examples of their potential impact in the field of science from the past years.

2012 grand prize went to Nithin Tumma, a student from Fort Gratiot, Michigan.

His research focused on certain proteins found in cancer cells. He discovered that by “inhibiting certain proteins, medical personnel may be able to slow the growth of cancer cells.” Tumma’s research has the potential to impact individuals who suffer from breast cancer. His research could lead to more effective and less toxic breast cancer treatments.

William Sun, of Chesterfield Missouri, won the second place prize (a $75,000 scholarship) in 2009.

He researched the molecule Golgicide A or GCA, “as a potential drug to inhibit intracellular transport of disease.” His discovery is said to impact the medical field when it comes to “preventing neurodegenerative diseases such as Alzheimer’s.”

In 2008, the grand prize winner was Shivani Sud from Durham, North Carolina.

Her research in the medical field was inspired by a close relative that was diagnosed with a brain tumor when Sud was six years old. With her research, Sud created a “50-gene model” to better identify tumors in high-risk cancer patients. With the model, doctors can also identify “the best therapeutic agents for treating [these] tumors.”

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