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Sunny You

Sunny You

2022 Davidson Fellow
$25,000 Scholarship

Age: 15
Hometown: Palmetto Bay, FL

Science: “Hurricane Convolutional Neural Network: A Novel Deep Learning Framework for Predicting Future Tropical Cyclone Intensity Using 20 Years of Satellite Rainfall Data”

About Sunny

I am Sunny You, a rising junior at Miami Palmetto Senior High School, which is located in Miami, Florida. After being forced to evacuate from home for 7 days due to Hurricane Irma in 2017, I became interested in how forecasters figured out how strong hurricanes would be.

I love STEM subjects and have been participating in math and science competitions since elementary school. I enjoy inspiring younger kids to get interested in scientific research by serving as a panelist and/or speaker for events hosted by the Science Department of Miami-Dade School District in Florida. In the future, I hope to continue pursuing research and hopefully become a professor in science or engineering.

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"To me, being a Davidson fellow is a huge accomplishment and honor."

Project Description

Hurricanes are one of the biggest threats to our growing coastal cities, causing major loss of life and property damage. As hurricanes continually become stronger and cause more damage due to the effects of climate change, our ability to forecast their intensity becomes ever more important. In my project, I designed a novel Hurricane Convolutional Neural Network (HCNN) model that can more accurately predict hurricane intensity than the currently used models for predictions up to a whole day in advance. My model applied advanced machine learning techniques into NASA satellite images and hurricane environmental predictors. It provides the potential to dramatically improve the accuracy of hurricane intensity forecasts, especially on major hurricanes and intensifying storms which are the most threatening to coastal communities.

Deeper Dive

For my project I developed a novel Hurricane Convolutional Neural Network (HCNN) model to accurately predict the intensity of hurricanes up to a day in the future. Over the past 40 years, hurricanes have caused $997 billion of damage in the United States alone. Since the intensity of a hurricane is directly related to the potential damage, correctly predicting its future intensity is very important for disaster mitigation. While it is true that the NOAA National Hurricane Center (NHC) has a suite of skillful models for predicting a hurricane’s track, operational intensity models are much less skillful. Predicting hurricane intensity is a great challenge for forecasters because it is not only controlled by many environmental factors, but also by each storm’s internal convective and rainfall structures. The Statistical Hurricane Intensity Prediction Scheme (SHIPS) is one of the most accurate models currently used by the NHC operationally for hurricane intensity forecasts. SHIPS is a multi-linear regression model mainly based on environmental predictors which do not sufficiently account for hurricane internal structures. In my research, I tackled this problem by leveraging machine learning and 20 years of NASA satellite rainfall images of hurricanes to create a model that predicts hurricane future intensity more accurately than SHIPS. I was inspired to pursue hurricane intensity research because I live in a coastal city (Miami, Florida) that is vulnerable to hurricanes every summer. After being forced to evacuate from home for 7 days due to Hurricane Irma in 2017, I became interested in how forecasters figured out how strong hurricanes would be. When I came across research papers about SHIPS, I felt that I could use machine learning to improve their model.

As I was completing this project, I faced many challenges, such as having to learn statistical analysis, how to use the Python TensorFlow library, and the R programming language for my project, along with the massive obstacles of data collection and time management. From this project, I have learned how to manage my workflow, incorporate and design machine learning models to solve big problems, and how to design a research project. I cannot thank my research mentor, Prof. Ping Zhu from Florida International University, enough for his consistent support of my project, especially for teaching me how to read and write scientific papers, and for his inspirational comments and suggestions to improve my model. Furthermore, I would like to thank my AP Environmental Science teacher and science fair sponsor, Ms. Pamela Shlachtman, and my AP Chemistry teacher, Dr. Yuria Sharp for their continuous support and encouragement to continue even through setbacks. I would also like to thank my AP Biology teacher Dr. Israel, AP Human Geography teacher Ms. Pizarro, AP Calculus teacher Mrs. Tuttle, AP Computer Science teacher Ms. Quintela, English teacher Mrs. Perse, school counselor Ms. King, and Miami-Dade school district science fair coordinators Mrs. Wendy Forteza and Mr. Carlos de la Camara for their unwavering support throughout my scientific inquiry and research journey. Overall, the pandemic didn’t affect my research very much, as my project was mostly done using online resources while at home.

My work will improve the quality of life for others by providing improved disaster response actions for coastal communities and cities vulnerable to hurricanes in the Atlantic Ocean. Since my HCNN model is significantly more skillful than the SHIPS model (13% more accurate on all storms, 15% more accurate on major hurricanes, and 6% more accurate on intensifying hurricanes), this project will allow for more informed disaster responses for these extreme tropical cyclones. As a result, this project will benefit millions of people who are all vulnerable to hurricanes in the US East Coast and the Caribbean. In the future, I also plan to make a fully-functioning web/mobile app to provide real-time hurricane predictions from my HCNN model to the general public and forecasters alike, along with expanding my project to other tropical cyclone-prone ocean basins like the Pacific and Indian Oceans.


If you could have dinner with the five most interesting people in the world, living or dead, who would they be?

If I could have dinner with any 5 people, I would have dinner with Dylan Lu (a pro Catan player), Issac Newton, Hikaru Nakamura (a grandmaster chess streamer), Terrence Tao, and Tord Reklev (a pro Pokémon player).

What is one of your favorite quotes?

One of my favorite quotes is: “Improvise, Adapt, Overcome.”

What is your favorite hobby?

My favorite hobby is playing board games with my friends and family.

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In The News

Palmetto Bay, Fla. – The Davidson Fellows Scholarship Program has announced the 2022 scholarship winners. Among the honorees is 15-year-old Sunny You of Palmetto Bay. You won a $25,000 scholarship for his project, Hurricane Convolutional Neural Network: A Novel Deep Learning Framework for Predicting Future Tropical Cyclone Intensity Using 20 Years of Satellite Rainfall Data. He is one of only 21 students across the country to be recognized as a 2022 scholarship winner.

Download the full press release here