Abigail Hsu is a high school student at Newark Academy in New Jersey. She has a strong interest in computer science, business, economics, and mathematics.
Academic Achievements and Entrepreneurship
Abigail is an International Baccalaureate Diploma Candidate. She also received the Top Startup Pitch award in the LaunchX Entrepreneurship Program. In addition, she was nominated for her school’s Honor Council. This group represents just 1% of students who uphold the school’s Honor Code.
Abigail founded TeenPod, a podcast that highlights talented local teens. Its episodes cover sports, hobbies, and careers. The podcast attracts more than 500 listeners per episode.
She also established MySportsFeedback, a platform that connects athletes and coaches. The platform provides personalised feedback using data. Abigail led four high school students in developing its minimum viable product (MVP). She also pitched the product to seed investors and maintained its website. The platform has more than 800 active users.
Furthermore, Abigail delivered a TED Talk on designing inclusive algorithms. Her talk drew on months of independent research and analysis of academic publications.
Business Experience and Community Service
During her internship at Sequoia Capital, Abigail researched companies across American, European, and Asian markets. She examined their go-to-market strategies, financial performance, and revenue growth. Her research included companies such as Bricsys and Snowflake.
Beyond her business experience, Abigail contributed to the Bloom Organisation as a tutor. She taught underprivileged students in China English grammar, pronunciation, and communication.
Research on Exam Stress and Machine Learning
Abigail’s research paper, “Quantifying Exam Stress Progressions Using Electrodermal Activity and Machine Learning,” was accepted for presentation at the 23rd IEEE International Conference on Bioinformatics and Bioengineering (BIBE). The paper was also published in the IEEE Xplore digital library.
Her research combines electrodermal activity data with machine learning to study changes in exam stress. This work explores how these methods can help researchers examine physiological responses to stress.
Congratulations to Abigail on this achievement!
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