NCSSM has again had more students recognized as Scholars in the Regeneron Science Talent Search than any other school participating in the competition.


NCSSM continues string of impressive performances in prestigious math and science competition

NCSSM students have done it again. Ten Residential students and two Online students have been named among 300 scholars in the 2024 Regeneron Science Talent Search, the nation’s oldest and most prestigious math and science research competition for high school seniors. Just like last year, this number is higher than any other high school in the competition. 

Students submit “​​original research in critically important scientific fields of study,” contest guidelines note, and each student named a scholar receives $2,000, with another $2,000 awarded to their high school per scholar. The NCSSM Online students worked with mentors at their local high schools, which will receive that prize money.

Per a press release from non-profit Society for Science, which owns and manages the competition, the Science Talent Search this year received more applicants than it had seen in over five decades. Nearly 2,200 students from 712 high schools across 46 states, Puerto Rico and 10 other countries entered the competition. 

“The 300 scholars came from 196 schools, which averages out to about one and a half scholars per school,” Amy Sheck, NCSSM’s Dean of Science, said after evaluating the numbers found in the 2024 Scholar Book created by the Society for Science. “That we produced 10 of those students is simply astonishing.”

As proud as Sheck is of that figure, she made it clear that NCSSM isn’t gloating. “We’re happy to have topped the list, of course, but this isn’t about who can produce the most scholars. More than anything, our achievement year-in and year-out in this competition proves that NCSSM is doing what we’ve always tried our best to do: give students the tools they need to fulfill their potential. Talented students and skillful mentors are clearly a winning combination.”

Of the 300 scholars, 40 will be named Regeneron Science Talent Search finalists on Jan. 24. Those finalists will move on to a weeklong competition (March 6-13) in Washington, D.C., where they will compete for more than $1.8 million in awards.

NCSSM’s 2024 Regeneron Science Talent Search scholars, their mentors, and project titles are are:

Sydney Yeboah (Timothy Anglin); A Docking Study and Modification of Eugenol To Increase Selectivity in Acetylcholinesterase Inhibition

Christina Zhao (Timothy Anglin); Rational Design and Synthesis of a PHD2 Inhibitor for Oral Treatment of Chronic Kidney Disease-Induced Anemia

Matthew Lee (Jonathan Bennett); Using Spectral Entropy as a Measure of Chaos To Quantify the Transition From Laminar to Turbulent Flow

Kaitlyn Jin (Michael Bruno); A Novel and Sustainably Synthesized Imine Resveratrol Analog as a Multi-Target-Directed Ligand for the Treatment of Alzheimer’s Disease

Siddharth Maruvada (Michael Bruno); Design, Synthesis and Testing of Novel Small Molecule Interleukin-6 Inhibitors for the Amelioration of Inflammatory Bowel Disease

Emmie Rose (Michael Bruno); Analyzing NOx Removal Efficiency and Washing Resistance of Iron Oxide-Decorated g-C3N4 Nanosheets Attached to Recycled Asphalt Pavement Aggregate

Arnav Meduri (Bob Gotwals); Deep Learning-Based Detection of Posterior Vitreous Opacities for Retinal Tear Prediction

Arnav Garg (Heather Mallory); Treating Anorexia Nervosa Using Fluoxetine and Olanzapine in the Model Organism Caenorhabditis elegans

Linda Xue (Kimberly Monahan); Social Isolation on Behavior and Physiology in the Model Gromphadorhina portentosa

Maruthi Vemula (Quran Karriem of Duke University via NCSSM Mentorship program);

Mitigating Information Asymmetry in Governmental Policies: An AI-Driven Approach

NCSSM Online students:

Angelika Wang (Cary Academy); Construction of Modified Speckle Optical Tweezers for Horizontal Particle Trapping in Air

Reyansh Bahl (Green Level High School); Mapping Soil Organic Carbon for Regenerative Agriculture and Reducing Atmospheric Carbon Using Multispectral Satellite Imagery and Machine Learning