Award Value: $250,000
City, State: Sammamish, WA

Christine Ye, 17, of Sammamish, analyzed the gravitational waves emitted from collisions between neutron stars (collapsed, super-dense stars) and black holes for her Regeneron Science Talent Search physics project. Scientists study the gravitational waves resulting from such collisions to estimate the mass of astronomical objects. Christine built a statistical model using data from a gravitational wave observatory (known as LIGO) and simulated future observations. Her work implies that a quickly spinning neutron star could be extra massive, making it larger than typical neutron stars, though still not as large as a small black hole. It also suggests that the spin of rapidly rotating neutron stars must be accounted for when determining their maximum mass.

Award Value: $175,000
City, State: Orefield, PA

Victor Cai, 18, of Orefield, determined to create a digital guide dog to help his visually impaired karate teacher, designed a short-range, distance sensing radar for his Regeneron Science Talent Search engineering project. To keep the cost low, Victor adopted the little used multiple frequency continuous wave radar concept and built his system using “software defined radio,” which allows him to control his radar with software instead of specialized hardware. Victor’s radar transmits simultaneous signals at two different frequencies and then calculates distance by measuring the phase difference between them. Victor refined his radar by writing two algorithms to prevent imprecise readings caused by spectrum leakage and to correct erroneous phase measurements, allowing him to achieve 12 cm accuracy using only a few kHz of bandwidth compared to 1 GHz used by traditional radar.

Award Value: $150,000
City, State: Stony Brook, NY

Amber Kaixin Luo, 18, of Stony Brook, created a computational tool to reveal how ribosomes move along a cell’s mRNA transcript to produce proteins for her Regeneron Science Talent Search computational biology and bioinformatics project. Her new approach, called RiboBayes, couples a powerful algorithm and statistical techniques to reveal vital information about ribosome pause sites. These critical regions where ribosomes pause to regulate and determine next steps in the gene expression are not yet well identified. Current algorithms are unable to efficiently and accurately locate these key pause sites from ribosome sequencing data on a large scale. By finding these crucial determinants of ribosome movement and having the ability to evaluate key components of protein synthesis, RiboBayes opens the door to discovering how changes in ribosome movement can directly influence any disease of interest, such as cancers and Alzheimer’s.

Award Value: $100,000
City, State: Bloomington, IN

Daniel Larsen, 18, of Bloomington, showed the abundance of Carmichael numbers for his Regeneron Science Talent Search mathematics project. Along with being intellectually interesting, prime numbers are crucial for cryptography where large primes help keep communication secure. A tool useful in finding primes is called Fermat’s little theorem, a test that all prime numbers pass. Carmichael numbers are those that pass this test yet are not actually prime, and so are sometimes called Fermat’s pseudoprimes. Daniel answered an important question about the abundance of Carmichael numbers, showing that for any number, there is always a Carmichael number hidden between it and its double, if the number is large enough. Daniel hopes his work will lead to a better understanding of these intriguing numbers.

Award Value: $90,000
City, State: Bellevue, WA

Neil Chowdhury, 18, of Bellevue, Washington, submitted a computational biology and bioinformatics project to the Regeneron Science Talent Search. To fit inside a cell’s nucleus, a long string of DNA wraps around proteins, called histones, to form chromatin, which further loops and coils to form a chromosome. One method of modulating this folding process is to chemically encode “marks” on the DNA string. Neil attempted to replicate chemical marking using molecular dynamics simulations of specific DNA polymers (large molecules). His computational project explored a modification of a specific histone implicated in colon cancer. Neil coded his simulation in Python, an open-source programming language, and data from the relevant colon cancer cell line. His work accurately reproduced recent experimental results and showed that the histone modification caused changes in compartmentalization and loop extrusion, two key processes regulating DNA organization in cells.

Award Value: $80,000
City, State: Austin, TX

Aseel Rawashdeh, 17, of Austin, developed an inexpensive way to kill the larvae of the mosquitos that spread viral illnesses, such as malaria, for her Regeneron Science Talent Search environmental science project. Aseel incorporated essential oils, a known larvicide, into baker’s yeast. This procedure avoided the many problems associated with using oils alone, which include their sensitivity to light and heat, the large dosage required to be effective and toxicity to non-targeted organisms. She found it to be simple to encapsulate a relatively large quantity of essential oils into yeast microcapsules, which the targeted larvae readily ate. Aseel demonstrated the high toxicity of three encapsulated essential oils (cinnamon, garlic and orange) to the targeted mosquito larvae and showed that ingesting the oils prevented any surviving larvae from developing into mosquitos. Equally important, the treatment appeared to be benign to algae and non-targeted insect larvae, though this still must be tested in a natural ecosystem.

Award Value: $70,000
City, State: Centreville, VA

Pravalika Gayatri Putalapattu, 17, of Centreville, submitted a Regeneron Science Talent Search computer science project designed to monitor surgeries in real time to help detect errors. Prompted by the accidental death of a close cousin due to a “tired, overworked, underpaid surgeon in India,” Pravi developed a system that uses machine learning to detect the surgical steps taken in the operating room. Using annotated video recordings of gall bladder surgeries, she trained her system to monitor the surgical tools used between video frames to identify what actions the surgeon is performing. The algorithm uses image segmentation and network optimizations to achieve a runtime that’s five times faster than current methods. Pravi believes this approach would allow surgeons to verify their actions as they perform gallbladder surgery and quickly detect errors.

Award Value: $60,000
City, State: Palo Alto, CA

Neil Rathi, 17, of Palo Alto used his Regeneron Science Talent Search behavioral and social sciences project to model how human minds optimize language on the word level for efficient communication. He found that the smallest meaningful unit of a word can convey multiple features. An example is how “ed” in the word “talked” signals both past tense and word completion. Neil looked at linguistic patterns that display this “informational fusion” to quantify the degree to which it occurs. He trained his machine learning model to search syntax datasets in four languages to test whether the tiny units are used less frequently, are less tightly fused, and whether they are more closely located when the fusion of two features is high than when fusion is low. Both premises held, suggesting that language may have evolved for efficient communication. His work is a step toward understanding how the human mind processes and produces language.

Award Value: $50,000
City, State: Glenwood, IA

Amara Orth, 18, of Glenwood, developed a method to identify vibroacoustic patterns of honeybees, which reflect the health of the hive, to predict hive collapse and help protect her family’s bee farm for her Regeneron Science Talent Search computational biology and bioinformatics project. Working at home and in the family barn, Amara measured the sounds and vibrations from the bees in 25 hives from August to November 2021, and then analyzed the data using a mathematical model she developed. Her system predicted bee colony health with 92% accuracy. She hopes this will provide beekeepers with an early warning for hive collapse and give them time to intervene. She plans to expand the sound library and make her system available to other Iowans

Award Value: $40,000
City, State: Euless, TX

Luke Robert Robitaille, 18, of Euless, untangled the entropy of simple braids for his Regeneron Science Talent Search mathematics project. Mathematical braids are a formal way of describing and tabulating the patterns that can arise from intertwining multiple lengths of string. Braids that intertwine lengths of string can become very complicated, and so mathematicians use the concept of topological entropy to compare braids to each other. Topological entropy describes how complicated a given braid is by assigning each braid a number that is always either positive or zero. In his work, Luke studied what are called simple braids. He showed that for low numbers of strands, most simple braids are orderly, but as the number of strands grows large, nearly all simple braids are chaotic. This shows that a random simple braid will never be too simple, topologically speaking, if you have a lot of strands braided together. Braid theory has recently been used to better understand the chaotic mixing of fluids.