PITTSBURGH, Nov. 16, 2013 /PRNewswire/ -- Months of dedication and hard work in science, technology, engineering and mathematics (STEM) paid off tonight for four students named National Finalists in the Siemens Competition in Math, Science & Technology, the nation's premier research competition for high school students. Ivan Paskov of Scarsdale, N.Y. earned the top honors and a $3,000 individual scholarship for research on personalized cancer treatments. Research on plants' resistance to ozone earned Priyanka Wadgaonkar, Woodmere, N.Y.; Zainab Mahmood, Hewlett, N.Y.; and JiaWen Pei, Valley Stream, N.Y. the $6,000 team scholarship.
The students presented their research this weekend to a panel of judges from Carnegie Mellon University, host of the Region Four Finals. They are now invited to present their work on a national stage at the National Finals in Washington, D.C., December 7-10, 2013, where $500,000 in scholarships will be awarded, including two top prizes of $100,000. The Siemens Competition, a signature program of the Siemens Foundation, is administered by the College Board.
"These incredible students have invested significant time and energy to advance research and exploration in critical fields," said David Etzwiler, CEO of the Siemens Foundation. "I commend the finalists for their outstanding achievements and wish them luck in the next phase of the competition."
The Winning Individual Ivan Paskov, a senior from Edgemont Junior/Senior High School in Scarsdale, N.Y., won the individual category and a $3,000 scholarship for his project entitled, Predicting Cancer Drug Response Using Nuclear Norm Multi-Task Learning.Ivan's mother was diagnosed with cancer when he was in fifth grade, so he channeled his initial shock and fear into determination to fight the disease through groundbreaking research. Since each cancer responds differently to an individual drug, Ivan explored those relationships to determine their complex interactions. Using a process inspired by the human brain, he was able to significantly increase the accuracy of drug response predictions, providing novel insights into personalized cancer treatments.
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