4 seniors named as Regeneron scholars


Courtesy of the Society for Science

Seniors Shray Alag, Saloni Shah, Aditya Tadimenti and Sidra Xu were named Regeneron scholars in the Regeneron Science Talent Search (STS) as part of the top 300 scholars out of 1,760 applicants across 611 schools and 49 states.

by Mark Hu, STEM Editor

Seniors Shray Alag, Saloni Shah, Aditya Tadimeti and Sidra Xu were named Regeneron scholars in the Regeneron Science Talent Search (STS) last week as part of the top 300 scholars out of 1,760 applicants across 611 schools and 49 states.

Each scholar and their school will receive $2,000 from the competition. Regeneron will name the top 40 finalists, who will compete for more than $1.8 million, on Jan. 21. Regeneron STS was founded in 1942 as a competition allowing high school seniors to submit their individual research in scientific fields of study. Contestants are judged on their research, academic achievements and promise as scientists. A full list of scholars can be found here.

Shray’s work examined 360,000 COVID-19 clinical trials using natural language processing to determine insights, such as disease to gene correlations, from those trials. His project was titled “Analysis of COVID-19 Clinical Trials: a Data-Driven, Ontology-based, Longitudinal, and Natural Language Processing Approach.”

“I wasn’t expecting it for sure, but I was really happy because it’s recognition that all your work pays off or has been seen as scientifically validated by some of the highest competition for research,” Shray said.

Saloni’s project, “Identifying Resilience Mutations in an Alzheimer’s Disease Whole-Genome Sequencing Cohort,” used various bio-computational tools to determine whether there were rare mutations in specific genes, and she identified eight genes that were significantly associated with Alzheimer’s.

“Being named a Regeneron semifinalist was validating to me, that the work that I’m doing is significant and important and that it can make a difference, and that other people can see that too,” Saloni said. “It was more of a joy that I could do these things rather than a joy that I was a semifinalist.”

Aditya’s research used machine learning to predict the size of wildfires based on factors such as meteorological variables, physical variables such as elevation and topography and socioeconomic variables at the fires’ start location. His project was titled “Machine Learning and Wildfire Burned Area: Examining Computational Techniques to Predict Fire Size for Practical Insights.”

“I was excited that I was recognized among other peers who have made key contributions to the scientific community,” Aditya said. “While being a semifinalist is great, I think that the greater value would be connecting with those other like-minded individuals because maybe in 10 or 15 years from now, we’d be changing the world in significant ways.”

Sidra’s project, titled “Application of Gene Embedding for Improved Somatic Mutation-Based Primary Cancer Typing and Biomarker Discovery,” focused on using a method from natural language processing called embedding to improve machine learning models to understand genes more deeply to classify different cancer types.

“It’s a great honor to be recognized among so many talented high school seniors in the nation,” Sidra said. “For my project to be considered among those 300, it validates a new scientific approach where scientists see not just biology, not just physics, not just chemistry as standalone disciplines, but rather as one whole unifying concept of science and multidisciplinary study.”