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Two Syosset Students Named 2025 Regeneron Science Talent Scholars
Two Syosset High School students have been named 2025 Regeneron Science Talent Search (Regeneron STS) Scholars. Congratulations to Syosset High School seniors Michael Ren and Winston Zhou. The Regeneron STS is the nation’s oldest and most prestigious pre-college science competition.
These students were selected from nearly 2,500 U.S. and international high school students who submitted original research in critically important scientific fields of study. They are among 300 students named Regeneron STS scholars and hope to be among 40 finalists named later this month. Each scholar will receive a $2,000 award with an additional $2,000 per scholar going to the high school to support STEM education. STS scholars are selected based on their exceptional research skills, commitment to academics, innovative thinking and promise as scientists as demonstrated through the submission of their original, independent research projects, essays, and recommendation.
“Our entire research team is incredibly proud of Michael and Winston for being recognized as scholars,” said Syosset High School lead research facilitator Heather Hall. “Their dedication, curiosity, and innovative thinking reflect the very best of what our students embody.”
Michael Ren conducted his research in-house. Winston Zhou was mentored by an outside researcher virtually while conducting his research in-house. Forty-one students who are part of the Syosset High School research program submitted projects, an increase from 27 last year.
Michael Ren completed his project, “Repurposing MALDI-TOF MS for Effective Antibiotic Resistance Screening in Staphylococcus epidermidis Using Machine Learning,” at Syosset High School under the direction of Ms. Erin O'Rourke. Michael's study combines machine learning with MALDI-TOF mass spectrometry to develop predictive models for antimicrobial resistance. The findings of his study demonstrate a remarkable advancement in fast, cost-effective antimicrobial resistance profiling, offering a promising solution for improving bacterial infection treatments in the future.
Winston Zhou completed his project, “Discrete Wavelet Multiview-Based Parallel Hybrid Deep Learning Model for Forecasting El Niño–Southern Oscillation Cycles,” at Syosset High School under the direction of Dr. Xiaodi Wang and Mr. Neal Hagan. Winston aimed to enhance El Niño-Southern Oscillation (ENSO) forecasting with a novel deep learning approach which integrates advanced mathematical techniques in a machine learning model. His hybrid model forecasted ENSO 9% more accurately than the current state-of-the-art short term forecasting models and is widely applicable in prediction models for other phenomena.
The 40 finalists in the competition, to be named on January 23, will undergo a rigorous judging process, interact with leading scientists, display their research for the public, meet with national leaders, and compete for more than $1.8 million in awards provided by Regeneron.