The Michigan Institute for Data Science Annual Symposium, “A Data-Driven World: Potential and Pitfalls,” took place October 11, 2017, in Rackham Auditorium and the Michigan League. The symposium featured prominent researchers whose work is on the leading edge of innovation and discovery in data-intensive science, as well as a poster competition highlighting data science research at U-M.
Cathy O’Neil is the author of the New York Times bestselling Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, which was also a semifinalist for the National Book Award.
She earned a Ph.D. in math from Harvard, was a postdoctoral fellow in the MIT math department, and a professor at Barnard College where she published a number of research papers in arithmetic algebraic geometry. She then switched to the private sector, working as a quantitative analyst for the hedge fund D.E. Shaw in the middle of the credit crisis, and then for RiskMetrics, a risk software company that assesses risk for the holdings of hedge funds and banks. She left finance in 2011 and started working as a data scientist in the New York start-up scene, building models that predicted people’s purchases and clicks. Cathy wrote Doing Data Science in 2013 and launched the Lede Program in Data Journalism at Columbia in 2014. She is a columnist for Bloomberg View.
Daniela Witten‘s research involves the development of statistical machine learning methods for high-dimensional data, with applications to genomics, neuroscience, and other fields. She is particularly interested in unsupervised learning, with a focus on graphical modeling.
Daniela is the recipient of a number of honors, including a NDSEG Research Fellowship, an NIH Director’s Early Independence Award, a Sloan Research Fellowship, and an NSF CAREER Award. Her work has been featured in the popular media: among other forums, in Forbes Magazine (three times), Elle Magazine, on KUOW radio, and as a PopTech Science Fellow. Daniela is a co-author (with Gareth James, Trevor Hastie, and Rob Tibshirani) of the very popular textbook “Introduction to Statistical Learning”. She was a member of the Institute of Medicine committee that released the report “Evolution of Translational Omics”. Daniela completed a BS in Math and Biology with Honors and Distinction at Stanford University in 2005, and a PhD in Statistics at Stanford University in 2010. Since 2014, Daniela is an associate professor in Statistics and Biostatistics at University of Washington.
James W. Pennebaker is a social psychologist with cross-disciplinary interests. For the last several years he has studied the relationship between people’s use of everyday language and their personality and social behaviors. The developer of the text analysis program LIWC, he and his students are discovering that the most forgettable words in most any language (e.g., pronouns, articles, prepositions) can detect people’s motivations, intentions, emotions, and thinking styles. More recently, he is overseeing Project 2021, a university-sponsored initiative to transform the future of undergraduate education. Author of 10 books and over 300 scientific articles, Pennebaker is among the most cited social scientists in the world.
Francesca Dominici is Professor of Biostatistics at the Harvard T.H. Chan School of Public Health and Co-Director of the Data Science Initiative at Harvard University. She is a data scientist whose pioneering scientific contributions have advanced public health research around the globe. Her life’s work has focused broadly on developing and advancing methods for the analysis of large, heterogeneous data sets to identify and understand the health impacts of environmental threats and inform policy.
Dr. Dominici received her B.S. in Statistics from University La Sapienza in Rome, Italy and her Ph.D. in Statistics from the University of Padua in Italy. She did her postdoctoral training with Scott L. Zeger and Jonathan M. Samet at the Bloomberg School of Public Health at Johns Hopkins University. In 1999, she was appointed Assistant Professor at the Bloomberg School of Public Health and in 2007 she was promoted to Full Professor with tenure. Dr. Dominici was recruited to the Harvard T.H. Chan School of Public Health as a tenured Professor of Biostatistics in 2009. She was appointed Associate Dean of Information Technology in 2011 and Senior Associate Dean for Research in 2013. She is currently the Co-Director of the Harvard Data Science Initiative.
Nadya T. Bliss is the Director of the Global Security Initiative (GSI) at Arizona State University. GSI serves as the university-wide hub addressing emerging security challenges, including borderless threats (cyber security, health security, and resource security). These challenges are often characterized by complex interdependencies and present conflicting objectives requiring multi-disciplinary research and cross-mission collaboration. GSI currently has approximately 150 faculty affiliates across 9 college-level units and is home to the Cybersecurity and Digital Forensics Center, the Human Security Collaboratory, Resilient Collective Systems Lab, and the DARPA Working Group. GSI also serves as the University’s interface to the Department of Defense and the Intelligence Community as well as ASURE (ASU Research Enterprise – off campus, classified-capable research facility). Prior to taking on the GSI role, Dr. Bliss served as the Assistant Vice President, Research Strategy in the Office of Knowledge Enterprise Development. Dr. Bliss holds a Professor of Practice appointment (and is a member of Graduate Faculty) in the School of Computing, Informatics, and Decision Systems Engineering; Senior Sustainability Scientist appointment in the Julie Ann Wrigley Global Institute of Sustainability; and affiliate appointments in the School for Future of Innovation in Society, the Center on the Future of War (collaboration between ASU and New America), and the Simon A. Levin Mathematical, Computational and Modeling Sciences Center. Dr. Bliss is also a Senior Fellow at New America. Before joining ASU in 2012, Dr. Bliss spent 10 years at MIT Lincoln Laboratory, most recently as the founding Group Leader of the Computing and Analytics Group. Under her leadership, the Group’s research portfolio included a wide-range of programs funded by DARPA, IARPA, ONR, NGA, USAF, ASD(R&E), and other U.S. Government sponsors.
In 2011, Dr. Bliss was awarded the inaugural MIT Lincoln Laboratory Early Career Technical Achievement award recognizing her work in parallel computing, computer architectures, and graph processing algorithms and her leadership in anomaly detection in graph-based data (presented annually to 2 employees under 35). She is the recipient of the R&D100 award (2011) for her work on PVTOL: Parallel Vector Tile Optimizing Library. She has also served on the DARPA (Defense Advanced Research Project Agency) ISAT (Information Science and Technology) advisory board where she co-chaired studies on Macro-Economics and Cyber Security and Science and Engineering of Functional Networks. Dr. Bliss received bachelor and master degrees in Computer Science from Cornell University, a PhD in Applied Mathematics for the Life and Social Sciences (Complex Adaptive Systems Science) from Arizona State University, and is a Senior Member of IEEE. Starting in July 2017, Dr. Bliss will serve a 3-year term on the Computing Research Association’s Computing Community Consortium (CCC) Council.