Tianyu Wang
About Tianyu Wang
Tianyu Wang is a research intern at NYU Langone Health and has a background in data science and mathematics, with experience in machine learning applications in medical imaging.
Research Internship at NYU Langone Health
Tianyu Wang currently holds a research internship position at NYU Langone Health. In this role, he has been actively involved in utilizing data science techniques to contribute to medical research since 2018. His work primarily focuses on machine learning applications within the healthcare sector, aiming to improve predictive models and overall treatment outcomes.
Education and Expertise in Data Science
Tianyu Wang completed his Master's degree in Data Science at New York University from 2017 to 2019. His academic pursuit equipped him with advanced knowledge in data analysis, machine learning, and predictive modeling. This educational background forms the foundation for his professional work in applying data science to medical research projects.
Research Assistant at Chinese Academy of Sciences
In 2017, Tianyu Wang worked as a Research Assistant at the Institutes of Science and Development, Chinese Academy of Sciences. Based in Beijing, China, he contributed to various research initiatives over a seven-month period. His role involved supporting scientific investigations and generating valuable data insights.
Bachelor's Degree in Mathematics and Computer Science
Tianyu Wang earned his Bachelor's degree in Mathematics and Computer Science from the University of Utah between 2011 and 2016. This academic foundation provided him with extensive knowledge in computational theory, algorithm design, and mathematical reasoning, which he later applied to his work in data science and machine learning.
Developed 3D Convolutional Neural Network Model
Tianyu Wang developed a 3D convolutional neural network model that significantly increased the accuracy of total knee replacement forecasting to 86% by integrating multiple models. This work highlights his proficiency in creating advanced machine learning models that can have direct applications in medical diagnostics and treatment planning.
Presentations at ISMRM Conferences
Tianyu Wang presented his research findings at the ISMRM 27th Annual Meeting & Exhibition, where he focused on advancements in machine learning applications in medical imaging. Additionally, he delivered a presentation at the ISMRM Workshop in 2018 on Machine Learning, Part II. These presentations demonstrate his active engagement in the academic and professional community.