Big Data Panelists
Please find information below about our panelists for the Big Data Interdisciplinary Dialogue event on April 3rd, 2018.
Vanessa Frias-Martinez is an assistant professor in the iSchool and an affiliate assistant professor in the Computer Science Department at the University of Maryland, College Park. She is the director of the Urban Computing Lab and she is also affiliated with the CLIP Lab, the Center for Geospatial Information Science and the Maryland Population Research Center. Her main research objective is to advance the field of data science for social good with a focus on enhancing decision making processes through data-driven approaches using novel sources of information. She received her M.Sc. and Ph.D. degrees in Computer Science from Columbia University. From 2009 to 2013, she was a researcher in the Data Mining and User Modeling Group at Telefonica Research in Madrid, Spain. Her research is funded by the National Science Foundation and the World Bank.
Furong Huang is an assistant professor of computer science. Huang’s research focuses on machine learning, high-dimensional statistics and distributed algorithms—both the theoretical analysis and practical implementation of parallel spectral methods for latent variable graphical models. Some applications of her research include developing fast detection algorithms to discover hidden and overlapping user communities in social networks, learning convolutional sparse coding models for understanding semantic meanings of sentences and object recognition in images, healthcare analytics by learning a hierarchy on human diseases for guiding doctors to identify potential diseases afflicting patients, and more.
Grant McKenzie is an assistant professor in the Department of Geographical Sciences, affiliate of the Center for Geospatial Information Science and member of the Human Computer Interaction Lab. Much of Grant's current research is focused on exploring computational, data-driven approaches to human activity behavior, investigating the relationship between place and space. The foundation of this work involves working with ‘big’ user-contributed as well as authoritative datasets, exploiting spatial, temporal, and thematic patterns within the data. Using a range of data mining and machine learning techniques, these "Semantic Signatures" are employed in the development of interactive (desktop and mobile) geovisualization, spatiotemporal activity prediction models, and place discovery applications. This ongoing work has driven his interests in issues related to geo-privacy and credibility of spatial information as well as the broader role that geographic information science plays at the intersection of information technologies and society.
Ed Summers is Lead Developer at the Maryland Institute for Technology in the Humanities (MITH). Ed has been working for two decades helping bridge the worlds of libraries and archives with the World Wide Web. During that time Ed has worked in academia, start-ups, corporations and the government. He is interested in the role of open source software, community development and open access to enable digital curation. Ed has a MS in Library and Information Science and a BA in English and American Literature from Rutgers University. He is also a PhD student in the UMD iSchool where he studies web archiving practices. Prior to joining MITH, Ed helped build the Repository Development Center (RDC) at the Library of Congress. In that role he led the design and implementation of the NEH funded National Digital Newspaper Program’s web application, which provides access to 8 million newspapers from across the United States. He also helped create the Twitter archiving application that has archived close to 500 billion tweets (as of September 2014). Ed created LC’s image quality assurance service that has allowed curators to sample and review over 50 million images. He served as a member of the Semantic Web Deployment Group at the W3C where he helped standardize SKOS, which he put to use in implementing the initial version of LC’s Linked Data service.
Tunay I. Tunca
Tunay Tunca is a Professor of Management Science and Operations Management at Robert H. Smith School of Business at University of Maryland. He received his MS in Financial Mathematics and PhD in Business Administration from Stanford University, MS in Management Science from the University of Rochester, and BS degrees in Electrical Engineering and Mathematics with honors from Bogazici University. Prior to joining University of Maryland, he was an Associate Professor of Operations, Information, and Technology at Graduate School of Business at Stanford University. Professor Tunca also held positions as a visiting scholar at the Sloan School of Business at Massachusetts Institute of Technology, Wharton School of Business at University of Pennsylvania, Yahoo Inc., and Hewlett-Packard. His research interests include economics of operations and technology management, operations management in the sharing economy, theoretical and empirical analysis of procurement contracts and processes, and forecasting, risk and financing in supply chains. His research has won awards and recognitions from INFORMS, M&SOM, POMS and CSAMSE. He is an Associate Editor for the journal M&SOM. He is the winner of several teaching awards at University of Maryland, including the 2014 Allen J. Krowe Teaching Excellence Award, and Distinguished Teaching Awards for 2015, 2016, and 2017.