THE TEAM

EXECUTIVE BOARD

Wesley Tian, President

Wesley is a senior studying computer science and data science. Previously, he's worked on applying machine learning to healthcare. He's passionate about making all living things happier. Outside of school, he enjoys running, hiking, and writing.

Jonathan Stroud, VP of Projects, Founder

Jonathan is a fourth year Ph.D. student in the department of Computer Science and Engineering (CSE). His research interests are in Machine Learning and Computer Vision, including deep learning, structured prediction, and knowledge representation.

Mukai Wang, VP of Education

Mukai is a senior majoring in data science engineering. He transferred to Michigan from Shanghai China in 2017. MDST opened his mind and played a critical role in leading him from novice to expert in data science. As the new VP of Education, he is responsible for providing valuable learning resources and leading tutorial series for beginners.

Seth Saperstein, VP of Communications

Seth is a senior studying data science, economics, and financial mathematics. His interests include game theory in machine learning, topological data analysis, and mobile app development.

Cory Laban, VP of Recruitment

Cory is a sophomore studying CSE and minoring in statistics. He is newly passionate about data science and data for social good. He will be hosting MDST bonding activities like pizza parties! trivia nights! and study table hangouts! Newcomers should talk to him about getting involved in MDST and learning data science basics.

Eris Llangos, VP of Finance

Eris is a senior studying financial mathematics and data science. He's a huge sports nerd and is planning on pursuing a career in investment banking. Eris is responsible for funding all arrangements to planned MDST events and finding new opportunities that interest all MDST members.

ADVISORY BOARD

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.