Aaron Hsieh
About Aaron Hsieh
Aaron Hsieh is an Undergraduate Research Assistant at NYU Langone Health, with prior experience as a Software Engineer Intern at Facebook and a Teaching Assistant at NYU Tandon School of Engineering.
Title
Aaron Hsieh currently holds the position of Undergraduate Research Assistant at NYU Langone Health. In this role, he contributes to significant research in computational neuroscience and neuroengineering.
Education and Expertise
Aaron Hsieh completed his Bachelor of Science degree in Computer Science at New York University from 2019 to 2023. He demonstrated strong academic performance at Los Altos High School, achieving a GPA of 3.98/4.00 and earning his High School Diploma in 2019. His educational background has equipped him with a robust foundation in computer science and machine learning, which he applies in his current research endeavors.
Professional Background
Aaron Hsieh has gained valuable experience through various internships and assistantships. He interned at Facebook as a Software Engineer in Menlo Park, California, for three months in 2021. Prior to that, he worked as a Teaching Assistant at NYU Tandon School of Engineering for one year from 2020 to 2021. Additionally, he was an intern at ScienceVR in Palo Alto, California, for two months in 2018. These roles have helped him develop practical skills in software engineering and teaching.
Research Contributions
Aaron Hsieh contributes to groundbreaking research on Sudden Unexpected Death in Epilepsy (SUDEP) at NYU Langone Health. Under the guidance of Professor Dr. Zhe Sage Chen, he leverages machine learning and deep learning techniques in his work. His research is conducted in the Computational Neuroscience, Neuroengineering & Neuropsychiatry Laboratory (CN3), where he aims to integrate computational neuroscience with advanced machine learning methods to address complex neurological problems.
Interests and Specializations
Aaron Hsieh has a keen interest in integrating computational neuroscience with machine learning to solve intricate neurological issues. His specialization includes applying machine learning and deep learning techniques to research in neuroengineering and neuropsychiatry. This unique combination allows him to contribute to innovative solutions in the field of neurological research.