I am currently pursuing my PhD in Industrial Engineering and Operation Research at Purdue University - my current research focus on online continuous non-convex optimization and its application in reinforcement learning.Prior to my endeavor back in academia, I have obtained my accelerated MS in Applied Statistics and BS in Statistical Science from the University of Michigan and Chinese University of Hong Kong joint program, and worked as a full stack data scientist, helping develop financial predictive models for fundraising and implement end-to-end pipelines with big data technologies and machine learning practices on the cloud, utilizing tools including but not limited to: Databricks, Google Cloud, AWS, Spark, SQL, R, Tableau and various machine learning and data engineering packages in Python. I also have extensive experience with non-technical business communication, accurately locating requests and delivering results to the satisfaction of our stakeholders.Feel free to connect with me if you are looking for interns or collabs in the relevant field of Data Science and Quantitative Finance.