Bronx Science High School names nine scholars and two finalists from the Regeneron Science Talent Search competition, Class of 2024.
Bronx Science Scholars Make Waves in Science and Mathematics
The Bronx High School of Science (Bronx Science) continues to produce exceptional students who are making significant contributions to the fields of science and mathematics. These Regeneron Science Talent Search Scholars have been recognised for their rigorous research projects that often combine biology, chemistry, physics, mathematics, and interdisciplinary subjects.
Jonathan Lin, a standout scholar, investigated the evolutionary patterns of microRNAs in 10 closely related species, discovering five distinct classes. Kun-Hyung Roh, another brilliant mind, built a machine learning model to predict drugs that reverse Alzheimer's Disease by inhibiting CtBP2 expression.
The school's advanced STEM offerings, including more than 100 unique courses such as AP and post-AP classes in biology, chemistry, physics, neuroscience, and other sciences, prepare its students to excel in prestigious science competitions like the Regeneron Science Talent Search. The school's emphasis on laboratory experience and research skills helps Bronx Science Regeneron Scholars stand out in highly competitive fields.
In fact, Bronx Science had nine students who were semi-finalists in the Regeneron Science Talent Search, the second highest number of selected students of any school featured. Sophie D'Halleweyn and Kun-Hyung Roh were named finalists in the competition.
Aiden Hightower, for example, found a new methodology for novel DNA motifs from DNA using the tensegrity triangle, creating his own crystals in the process. Rachel Wu studied the ability of social media content to influence its audience, identifying features that can detect fake news. Melody Jiang studied how a certain immune cell, Natural Killer Cell (NKCs), interacts with bone marrow-derived mesenchymal stromal cells (MSCs), thereby encouraging the former's development. Ryan Kim's research focuses on enhancing the reprogramming of endothelial cells for liver regeneration therapy using lentiviral reprogramming.
Nema Khan analysed the effects of news reports on the occurrence of mass shootings, concluding that a rise in news reports with the words "mass shootings" may precipitate an increase in mass shootings. Dimitrios Mahairas designed a machine learning model to identify millions of plant species, aiding in the discovery of new antibiotics and the protection of ecosystems.
These scholars have diverse hobbies that inform their interests and studies, such as dancing, reading Russian literature, and running. Dr. Scott Savaiano, a teacher at Bronx Science, encourages students to follow in the scholars' footsteps and pursue research.
Kun-Hyung Roh emphasised the importance of asking "why" in research and the value of discoveries and innovations beyond medals and trophies. The Regeneron Science Talent Search highlights studies with worldwide impact, including models working towards a cure of celiac disease, robots, satellites, and governmental analysis.
All scholars intend to continue immersing themselves in scientific pursuits after graduation, demonstrating a commitment to advancing their fields. The Regeneron Science Talent Search is an annual science and mathematics competition for high school seniors, awarding $1.2 million to 300 students across 36 states and China.
In summary, Bronx Science’s Regeneron Scholars represent a distinguished group of young scientists excelling in rigorous scientific research and mathematics, supported by one of the nation’s strongest STEM high school programs, thereby contributing to the advancement of their fields through competitions like the Regeneron Science Talent Search.
- The students at Bronx Science, such as Jonathan Lin and Kun-Hyung Roh, have been recognized for their research projects that integrate various fields like biology, chemistry, physics, and mathematics.
- Rachel Wu, a scholar at Bronx Science, has conducted research on social media content and discovered features that can help detect fake news.
- Melody Jiang's research at Bronx Science focuses on studying the interaction between Natural Killer Cells and bone marrow-derived mesenchymal stromal cells.
- Dimitrios Mahairas, a student from Bronx Science, has designed a machine learning model to identify millions of plant species, potentially aiding in the discovery of new antibiotics and the protection of ecosystems.
- Nema Khan, a student at Bronx Science, has analyzed the effects of news reports on the occurrence of mass shootings, finding that an increase in news reports with the term "mass shootings" might lead to an increase in actual mass shootings, indicating a connection between media coverage and social issues.
