Yinpu Li
About Yinpu Li
Yinpu Li is a Research Scientist with a PhD in Statistics from Florida State University. Currently employed at Convoy Inc, Li specializes in deep learning and modern machine learning techniques to enhance decision-making processes.
Work at Convoy
Yinpu Li has been employed as a Research Scientist at Convoy Inc since 2021. In this role, Li applies advanced skills in deep learning and modern machine learning techniques to enhance decision-making processes within the company. Based in Seattle, Washington, Li contributes to various research initiatives that aim to optimize logistics and supply chain operations.
Education and Expertise
Yinpu Li holds a Doctor of Philosophy (PhD) in Statistics from Florida State University, where they studied from 2017 to 2021. Prior to this, Li earned a Master's degree in Statistics from The George Washington University from 2015 to 2017, and a Bachelor of Science (B.S.) in Statistics from East China Normal University from 2010 to 2015. Li specializes in matching mechanisms and possesses expertise in applying modern machine learning techniques.
Previous Work Experience
Before joining Convoy, Yinpu Li gained valuable experience in various internships and roles. Li worked as a Statistics and Quantitative Sciences Intern at Takeda for two months in 2021 and as a Mathematical Sciences Research Intern at the National Institute of Standards and Technology (NIST) for three months in 2020. Additionally, Li served as a Research Assistant at Florida State University from 2019 to 2020 and as an Instructor from 2018 to 2019. Li also completed a Data Analyst Internship at Fiat Chrysler Automobiles (FCA) in Shanghai from 2013 to 2014.
Research Contributions
Yinpu Li's research contributions primarily focus on the application of deep learning and machine learning techniques. Li specializes in matching mechanisms, which are integral to their research work. This expertise supports the development of innovative solutions in the field of statistics and data analysis, enhancing the understanding of complex data sets.