Jackson Sargent, President

Jackson is a Junior studying Computer Science Engineering and Data Science Engineering, minoring in Political Science. He’s interested in all kinds of applications of machine learning and artificial intelligence. In his free time he enjoys rock climbing, hiking, and reading. If you have any questions about MDST, feel free to reach out.

Naitian Zhou, VP of Projects

Naitian is a junior studying computer science and data science. His interests include computational linguistics and maintaining a rigid sleep schedule. Outside of MDST, he contributes to the Michigan Daily and Blueprint Literary Magazine.

Renee Li, VP of Education

Renee is a junior studying data science and electrical engineering. Passionate about both programming and playing with (well, breaking) electronics, she is interested in how we can leverage technology and the data we get from it to solve real-world problems. She works on developing and hosting educational workshops for MDST members--though she still has a lot to learn herself!

Iris Derry, VP of Communications

Iris Derry is a junior studying computer science. She is still figuring out what she wants to do after college, but she loves playing video games and chilling with friends in her free time. MDST was the first club she joined at umich because of the welcoming environment and wants to be apart of the growth of the organization.

Jed Pienkny, VP of Recruitment

My name is Jed, and I am the VP of recruitment for the coming year! I am majoring in Electrical Engineering with a math minor, but am very interested in the field of data science as a whole. I currently do research in NERS regarding gamma-ray imaging while working on other side projects. I enjoy video games and cooking (cliché, I know), and I'm looking forward to labs reopening so I can work on some projects (I'm still in Ann Arbor, despite living in Brooklyn, NY). I joined MDST to learn more about data science and work on interesting projects, and I haven't been disappointed. Looking forward to working with you this coming year!

Anthony Ng, VP of Finance

Anthony is a junior studying computer science with a minor in business. As VP of Finance, he is responsible for funding all arrangements to planned MDST events and finding new opportunities that interest all MDST members. In his free time, Anthony enjoys playing piano, trying new foods, and getting boba with his friends!


Eric Chen, Project Committee

Eric Chen is a junior studying data science with a minor in math. He is passionate about using data science for social good and hopes to use his skills to make a positive impact. His interests include game theory and world history, among other things. Ask him about: jazz piano, swimming, and how he can put his foot behind his head!

Ahmed Khan, Project Committee

Ahmed is a Junior studying Computer Science. He is interested in cyber security and game development. Outside of school, he enjoys reading and playing sports.

Simona Hendl, Social Committee

Simona is a sophomore planning on majoring in Information Sciences and Organizational Studies and is new to the world of Data Science. As a member of the Social Committee, she is excited to plan and host fun social bonding events for MDST members. Outside of MDST, she works for The Michigan Daily and is a Student Ambassador for U-M.

Stuart Coles, Social Committee

I'm Stuart Coles, a rising junior double-majoring in Data Science and music. I was drawn to MDST because of the community and the opportunity to work on real projects, and I'm excited to help others do the same and making great personal connections doing it.


Jenna Wiens, Ph.D., Advisor

Jenna Wiens is a Morris Wellman Assistant Professor of Computer Science and Engineering (CSE) at the University of Michigan in Ann Arbor. She currently heads the Machine Learning for Data-Driven Decisions (MLD3) research group. Her primary research interests lie at the intersection of machine learning and healthcare. The overarching goal of her research agenda is to develop the computational methods needed to help organize, process, and transform data into actionable knowledge. She received her PhD in 2014 from MIT.

Eric Schwartz, Ph.D., Advisor

Professor Eric Schwartz's expertise focuses on predicting customer behavior, understanding its drivers, and examining how firms actively manage their customer relationships through interactive marketing. His research in customer analytics stretches managerial applications, including online display advertising, email marketing, video consumption, and word-of-mouth. He earned his Ph.D. in Marketing from the Wharton School and a B.A. in Mathematics and Hispanic Studies, all from the University of Pennsylvania.

Danai Koutra, Ph.D., Advisor

Danai Koutra is an Assistant Professor in Computer Science and Engineering at University of Michigan, where she leads the Graph Exploration and Mining at Scale (GEMS) Lab. Her research interests include large-scale graph mining, analysis of multi-source network data, graph summarization, similarity and matching, and anomaly detection. Danai's research has been applied mainly to social, collaboration and web networks, as well as brain connectivity graphs. She earned her Ph.D. and M.S. in Computer Science from CMU in 2015 and her diploma in Electrical and Computer Engineering at the National Technical University of Athens in 2010.

Yang Chen, Ph.D., Advisor

Yang Chen received her Ph.D. (2017) in Statistics from Harvard University and joined the University of Michigan as an Assistant Professor of Statistics and Research Assistant Professor at the Michigan Institute of Data Science (MIDAS). She received her B.A. in Mathematics and Applied Mathematics from the University of Science and Technology of China. Research interests include computational algorithms in statistical inference and applied statistics in the field of biology and astronomy.

Jonathan Terhorst, Ph.D., Advisor

Jonathan Terhorst received his Ph.D. (2017) in Statistics from UC Berkeley and joined the University of Michigan as an Assistant Professor of Statistics. He is broadly interested in applications of statistics and machine learning to problems in biology, with a particular emphasis on statistical and population genetics.