George D. Yancopoulos Innovator Award

George D. Yancopoulos, MD, PhD Regeneron President and Chief Scientific Officer
George D. Yancopoulos, MD, PhD
Regeneron President and Chief Scientific Officer

George D. Yancopoulos, MD, PhD, has built and managed Regeneron alongside Dr. Schleifer for over 30 years. Dr. Yancopoulos is currently President, Chief Scientific Officer and Co-Chair of Regeneron’s Board of Directors. Dr. Yancopoulos, along with key members of his team, is the principal inventor of Regeneron’s nine FDA-approved drugs and foundational technologies, including the TRAP technology, VelociGene® and VelocImmune®. He has been named an Ernst & Young Entrepreneur of the Year and has been pivotal in creating the science-driven, collaborative and highly-productive R&D culture at Regeneron. This unique environment has earned the company widespread recognition, including repeatedly being named one of the “most innovative companies in the world” by Forbes magazine.

Dr. Yancopoulos was the 11th most highly cited scientist in the world in the 1990s, and in 2004 he was elected to be a member of the National Academy of Sciences. He has also driven Regeneron’s commitment to STEM education, which includes robust internship and mentoring programs. He spearheads the company’s support for the Regeneron Westchester Science and Engineering Fair in New York’s Hudson Valley, the Regeneron Prize for Creative Innovation for top graduate and postdoctoral students, the Regeneron Science Talent Search and the Regeneron International Science and Engineering Fair.

Regeneron and Society for Science are pleased to present an award of $75,000 to the top First Place project. The George D. Yancopoulos Innovator Award recognizes the best of the best among the outstanding students from around the world who participate in Regeneron ISEF. The winning project is selected on the basis of outstanding and innovative research, as well as on the potential impact of the work — in the field and on the world at large.

2023 ISEF - Kaitlyn Wang 17, of San José, CA, won first place and received the $75,000 George D. Yancopoulos Innovator Award

2023

Kaitlyn Wang, The Harker School, CA, United States of America

Kaitlyn Wang won first place and received the $75,000 award for finding an efficient way to identify certain exoplanets that orbit very closely around their stars. Previous techniques used to detect these ultra-short-period planets required enormous computational power but were not as effective at identifying these planets. Kaitlyn surmounted that problem by creating a special algorithm that runs on cheap hardware and results in much faster and higher-precision findings. Using her research, she says she found the smallest of these planets ever discovered.

Video

PHYS056 — Discovery of the Smallest Ever Ultra-Short-Period Planet Using Novel Phase Folding Detection System Parallelized on a Cheap GPU

 

 

Robert Sansone, Fort Pierce Central High School, FL, ISEF 2022

2022

Robert Sansone, Fort Pierce Central High School, FL, United States of America

Robert Sansone won first place and received the $75,000 award for his research that improved the torque (rotational force) and efficiency of synchronous reluctance motors, which are rugged, efficient, magnet-free alternatives to traditional permanent magnet motors. He hopes his research will lead to the proliferation of electric vehicles that do not require magnets made from economically and environmentally unsustainable rare-earth elements.

Video

ETSD014 – First Insights into a Novel Synchronous Reluctance Electric Motor Design

 

Michelle Hua, Cranbrook Kingswood School, MI, USA, ISEF 2021

2021

Michelle Hua, Cranbrook Kingswood School, MI, United States of America

Michelle Hua won first place and received the $75,000 award for her discovery of an artificial intelligence-based algorithm used for human action recognition. Using human silhouettes, she designed and implemented a novel deep learning framework that outperforms all similar state-of-the-art algorithms.

Video

ROBO033 — Dilated Silhouette Convolutional Neural Network: A Novel Deep Learning Framework for Real-time Human Action Recognition