Welcome to my personal website!
My name Yinwei Zhang. I am a Ph.D. candidate at the University of Arizona majoring in Industrial Engineering. The University of Arizona locates in Tucson, southwestern America. The weather is super dry and the temperature is crazy here during the summer, so we don’t have many green trees but saguaro cactus here.
About my Ph.D. career
I have been studying at the University of Arizona for 7 years. I first came here as a master’s student in the Department of Systems and Industrial Engineering. This department is famous for its operation research and quality engineering. After I got my master’s degree, I started to pursue my Ph.D. degree in Industrial Engineering. During my Ph.D. career, I focused on spatial-temporal modeling and anomaly detection in high dimensional data by using statistics and machine learning knowledge. Since my research area is closely related to statistics, I pursued another master’s degree in Statistics and Data Science since 2020. This program solidates my understanding of concepts such as probability, hypothesis tests, regression, classification, and experimental design. In Aug/2022, I passed the qualifying exams with a Ph.D. level pass and I earned my second master’s degree in Dec/2022.
About my internship
From May/2023 to Aug/2023, I worked as a machine learning engineering at CVS Health. In this 3-month internship, I worked with my mentor and different teams to deliver models/products, with a particular focus on MLOps and Large Language Model as Services. The tools I used include Google Cloud Platform, docker container, Jenkins, Airflow, and FastAPI. This is an amazing experience as my colleagues are super nice and would like to share their experiences with me. What’s more, I finally had a chance to visit New York.
From Jan/2020 to Aug/2021, I worked as a research scientist at ABB, Raleigh. The main tasks for me were applying deep learning algorithms to solve real-world vision-based industrial applications. The tools include Python, TensorFlow, and PyTorch. At the beginning of the internship, due to the pandemic, obstacles occurred as we have limited data and limited hardware resources. However, with the help of my project manager, we began to make significant progress in improving the prediction accuracy of the deep-learning methods. I rotated between two research groups for different applications and contribute to the teams. At the end of the internship, the achievements I made were summarized into several patents which are now under filing.
About my soft-skills
During my internship and research career, I am always a quick learner, and ready to get my hands “dirty”. One example is the project for the autonomous vehicle. This project requires me to integrate ROS (robotic operating system) with Autoware and Carla such that the data can be simulated. It is likely the most challenging project I have worked on as all three platforms are new to me and there are few documents about such integration. Although I met tons of errors when I was trying to build the simulation pipeline, the good news is that I finally did it and now I am quite comfortable in using them. All of these were done in two months. With such experience, I believe I am capable of learning new tools quickly.
About my life
Besides my work, I really enjoy music and playing guitar. My favorite guitarist is Slash. Luckily, I had a chance to watch a Guns N’ Roses concert in Phoenix, AZ. Slash played like a killer. I also like photography and bring my camera with me all the time.
These are all about me. I appreciate that you read through all of these, thank you!