SOFIA TOMOV
I am passionate about solving problems and helping others.
I am currently enrolled as a dual enrollment student at the University of Tennessee in Knoxville. As an aspiring computer scientist, I have pursued projects on algorithms for genomic analysis as well as machine learning.
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2018 Intel ISEF First Place winner (Translational Medicine)
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2017 first place winner in international Project Paradigm Challenge (ages 9-13)
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2016 Caroline D. Bradley Scholar
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2016 finalist for the Discovery Education/3M Young Scientist Challenge.
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Recognized by Business Insider as one of "15 Young Prodigies Who Are Already Changing the World,"
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Work has been featured in US News and World Report and The Telegraph (UK).
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Founded Qardian Labs, a business that builds on the heart disease diagnostic software I developed that won First Place at Intel ISEF
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Founded Teen Vote, a nonprofit dedicated to lowering the voting age and promoting civics education, as well as volunteered teaching science and engineering to elementary students
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Started a local chapter of Project CS Girls, an organization dedicated to empowering middle and high school girls to change the world with computer science
MY PROJECTS
Make The Pill Fit the Ill
Prescription drug side effects are the 4th leading cause of death in the U.S. I wondered why people respond differently to the same drug, and found that genetic mutations affect a person's response. I innovated a type of computer algorithm, or problem solving procedure, to find mutations in a patient's genome. I was contacted by the medical software company Tabula Rasa Health Care for this research, and presented at their headquarters.
On with the Wind
Fossil fuel combustion harms human health. While experts agree that wind power is a viable alternative, inaccurate predictions of turbine power output waste energy and money. To address this problem, I innovated a way to improve the accuracy of turbine power output predictions using machine learning. Machine learning is a type of artificial intelligence that teaches the computer to learn from existing data and predict outcomes for future data.
Heart Smart
Heart disease is the number one killer worldwide. An accurate and early diagnosis can save lives by ensuring that patients receive treatment when they need it. I developed a software tool that uses a novel deep learning approach to generate quick and precise diagnoses. My innovation, HEARO - Heart Evaluation for Algorithmic Risk-reduction and Optimization, is a variable-layer deep neural network with the regularization optimization. This algorithm achieves results superior to previously published research, including those from Stanford University.