Health Data Science Testimonials
Learn More About the MS Health Data Science Program
Kaiyu Zhang, '22
Data Scientist, Camping World
“As a data scientist at Camping World, I can confidently say that the MS. Biostatistics, Health Data Science (HDS) program at the University of Michigan has been instrumental in shaping my experience and career.
"The HDS program's focus on applying statistical and computational methods to solve real-world healthcare problems has been particularly valuable in my work. Through the program's coursework and hands-on projects, I gained a deep understanding of the challenges and opportunities involved in analyzing and interpreting sales data. Additionally, the program's emphasis on collaboration and communication skills has enabled me to work effectively with cross-functional teams at Camping World, including business analysts, IT professionals, and marketers.
"The program has equipped me with the skills to communicate technical information in a way that is easily understandable by a non-technical audience, which has been critical in my work. I strongly recommend this program to anyone interested in pursuing a career in data science, particularly in healthcare."
Spencer Haupert, '22
Statistician, Food and Drug Administration
"I chose to pursue the Health Data Science concentration because I was excited to learn about the cutting-edge methods people are using to process and analyze big data. During my time in grad school, I learned machine learning techniques, cluster computing, R package development and more in addition to the foundational statistical theory and methods. I’m happy to report that the skills I learned have been invaluable in my current role. Knowing how to work with large quantities of data is becoming increasingly important, including in the pharmaceutical/regulatory space. I’m happy I chose Health Data Science and I’m confident its preparation will serve me well throughout my career."
Lingxuan Kong, '22
PhD Student in Biostatistics, University of Michigan
“As a student majoring in biostatistics, HDS concentration provides me with a broader view of research. The courses in HDS concentration helped me build my skills in computing and making my statistical tools. Before I took BIOS 625 and BIOS 629, which are two courses in the HDS concentration, I had no experience in using LINUX commands and building packages. I received comprehensive tutorials and helpful instructions when I was exposed to these brand-new areas. I also learned several new models such as generalized additive model (GAM). In the course projects, I experienced the whole procedure of doing a project designed by myself. I explored a real medicine database that contains millions of records and set up my own research goal. During the process, I had a chance to apply the techniques and models I learned from the HDS concentration courses to the analysis of data. My journey in the HDS concentration was fulfilled with the joy of stepping into a new area and learning useful techniques. The computing skills I learned in the HDS concentration make it possible for me to deal with large datasets or become an R package developer in the future.”
Yuan Zhong, '22
PhD Student in Biostatistics, University of Michigan
“The HDS program definitely built my foundation in this rapidly growing field. The comprehensive curriculum balanced theory and application so that I could perform data analysis with solid statistical reasoning. I am grateful that all my professors are knowledgeable and responsive to my questions and feedback. As someone working in the field, I found all the computing courses offered particularly beneficial, as they enhanced my ability to handle big data with advanced computing skills. The techniques I learned in the program have proven essential and practical in my current work, and I believe they will continue to be valuable in the future.”
Bangyao Zhao, '21
PhD Student in Biostatistics, University of Michigan
“The HDS program was an excellent academic experience. We took courses in data science, biostatistics, epidemiology, health informatics, and other related fields. In those courses, we had plenty of opportunities to discuss with professors and teaching assistants, collaborate in groups, and obtain hands-on project experience. Converting what we learned from textbooks to statistical thinking through communication and fun projects was a fascinating experience. We were also exposed to big data that required advanced programming skills, parallelized cluster computing, and GPU computing. We do cool visualizations to endow data with meaning. We also derived and implemented statistical computing algorithms while considering the computational feasibility.
From a student's perspective, these offered in-demand skills in health data science-related industries.
Overall, after the HDS program, I have gained a broad range of knowledge and skills related to health data science. The statistical training and research skills laid a solid foundation for me to pursue a Ph.D. degree. Although I eventually chose the path to Ph.D., what I learned from the HDS program has also made me competitive in health data science-related occupations."
Chen Chen, '22
PhD Student in Biostatistics, University of Toronto
“Through the health data science concentration program, I had opportunities to analyze high-dimensional and mobile health data and use machine learning algorithms to identify clinically meaningful patterns that can be used to inform clinical decision-making and improve patient outcomes. Many data scientists with computer science backgrounds have excellent skills in improving prediction accuracy and computational efficiency, while biostatisticians are critical in ensuring that clinical biomarkers and correct comparison groups are considered in health data science research. One of the most impactful projects I've worked on involved analyzing brain imaging data to identify patients who were diagnosed with Alzheimer’s disease. This motivated my research interest in joint models with imaging data and survival outcomes and now I am a biostatistics Ph.D. student at the University of Toronto. I'm grateful to be a part of this exciting field and can't wait to see what the future holds.”