Jane Li, President
Jane Li is a second-year master's student in the Department of Biostatistics. She is working on developing skills in data science and hopes to use those skills to advance healthcare and medicine. Previously, she had worked in groundwater remediation in Ann Arbor and gained an appreciation for working with chemistry data and learning about science through the lens of data analytics.
Naitian Zhou, VP of Projects
Naitian is a sophomore studying computer science and data science. His interests include computational linguistics and maintaining a rigid sleep schedule. Outside of MDST, he is a contributor and editor for Blueprint Literary Magazine.
Yi Zhang (Zack), VP of Education
Zack is a junior majoring in CS and Stats. He is passionate making an impact with data science and machine learning. As the VP of Education, he facilitates the workshops and welcomes any questions. Fun fact, he is a certified cook.
Sara Colom, VP of Communications
Sara Colom is PhD student in Ecology and Evolutionary Biology. She is passionate about applying Data Science and programming to analyze and quantify the complexities of the natural environment--especially in the field of evolutionary ecology. She is happy to learn and mentor in biology/data analysis/coding. In her free time she loves to play soccer and go on hikes.
Aman Srivastav, VP of Recruitment
Aman is a sophomore studying CSE and is new to the world of Data Science. He will be hosting social bonding events from pizza parties to study table hangouts. Let him know if you have any questions about joining MDST or want free MDST swag!
Jackson Sargent, VP of Finance
Jackson is a sophomore studying CSE and minoring in Political Science. He's interested in Computational Law and other interdisciplinary applications for Computer Science. Jackson is responsible for funding all arrangements to planned MDST events and finding new opportunities that interest all MDST members.
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 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.