Teen scientist researches new approach to neurological damage, wins Regeneron Science Talent Search 2017 | Society for Science & the Public
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The top three winners of the 2017 Regeneron Science Talent Search at the Awards Gala on March 14.
PHOTO COURTESY OF SOCIETY FOR SCIENCE & THE PUBLIC/CHRIS AYERS.
Regeneron STS
Young & Amazing

Teen scientist researches new approach to neurological damage, wins Regeneron Science Talent Search 2017

March 15, 2017

Forty finalists took home more than $1.8 million in awards at the Regeneron Science Talent Search 2017. Their scientific research ranged from improving biodegradable battery life to finding ways to eliminate space debris.

Indrani Das studied a possible approach to treating the death of neurons due to brain injury or neurodegenerative disease.
Indrani Das studied a possible approach to treating the death of neurons due to brain injury or neurodegenerative disease.
Photo courtesy of Society for Science & the Public/Chris Ayers.

Indrani Das, 17, of Oradell, New Jersey, won the top award of $250,000 in the Regeneron STS for her study of a possible approach to treating the death of neurons due to brain injury or neurodegenerative disease.

A contributor to neuron death is astrogliosis, a condition that occurs when cells called astrocytes react to injury by growing, dividing and reducing their uptake of glutamate, which in excess is toxic to neurons. In a laboratory model, she showed that exosomes isolated from astrocytes transfected with microRNA-124a both improved astrocyte uptake of glutamate and increased neuron survival.

Aaron Yeiser developed a new mathematical method for solving partial differential equations on complicated geometries.
Aaron Yeiser developed a new mathematical method for solving partial differential equations on complicated geometries.
Photo courtesy of Society for Science & the Public/Chris Ayers.

The second place honors and $175,000 went to Aaron Yeiser, 18, of Schwenksville, Pennsylvania, for his development of a new mathematical method for solving partial differential equations on complicated geometries. Partial differential equations are ubiquitous in science and engineering and are currently solved using computers. Aaron developed a more efficient way to do this and applied it to the challenging field of computational fluid dynamics.

Arjun Ramani blended graph theory with computer programming to answer questions about networks.
Arjun Ramani blended graph theory with computer programming to answer questions about networks.
Photo courtesy of Society for Science & the Public/Jessica Yurinko.

Arjun Ramani, 18, of West Lafayette, Indiana, won the third place award of $150,000 for blending graph theory with computer programming to answer questions about networks. These questions require statistical comparisons to hundreds or thousands of random graphs. Arjun developed an algorithm that greatly accelerated the process by reducing the time required to generate these graphs.

Read the full press release.