Speakers

Our speakers are an essential element to what makes our conference special. We seek out the widest range of experts to ensure a broad spectrum of discussion. This year, we are honored to present the following group of speakers.

KEYNOTE SPEAKER: Duncan Watts

Duncan Watts is a principal researcher at Microsoft Research and a founding member of the MSR-NYC lab. He is also an AD White Professor at Large at Cornell University. Prior to joining MSR in 2012, he was from 2000-2007 a professor of Sociology at Columbia University, and then a principal research scientist at Yahoo! Research, where he directed the Human Social Dynamics group.

His research on social networks and collective dynamics has appeared in a wide range of journals, from Nature, Science, and Physical Review Letters to the American Journal of Sociology and Harvard Business Review, and has been recognized by the 2009 German Physical Society Young Scientist Award for Socio and Econophysics, the 2013 Lagrange-CRT Foundation Prize for Complexity Science, and the 2014 Everett Rogers M. Rogers Award.

Watts holds a B.Sc. in Physics from the Australian Defence Force Academy, from which he also received his officer's commission in the Royal Australian Navy, and a Ph.D. in Theoretical and Applied Mechanics from Cornell University.

Discovery Leaders

Discovery Sessions are a unique aspect of our conference. In each Discovery Session, six Leaders present and discuss their work and opinions with fellow attendees in a shared setting. We're excited to have these folks leading this year's sessions.

Peter Barnes | LLNL
Dr. Peter D. Barnes currently leads the Network Simulation team, which is developing tools to simulate realistic computer networks, with realistic traffic models, at scale, meaning 10,000-10,000,000 simulated computers. With colleagues and collaborators at RPI, Dr. Barnes, recently set a pair of world records in discrete event simulation: achieving 504 billion simulation events per second, utilizing 7,864,320 MPI tasks on 1,966,080 compute cores. Dr. Barnes earned a B.S. in Physics from Yale University, and a M.S. and Ph.D. in Physics from the University of California, Berkeley.

Matthew Brashears | University of South Carolina
Matthew E. Brashears is an Associate Professor of Sociology. His current research focuses on linking cognition to social network structure, studying the effects of error and error correction on diffusion dynamics, and using ecological models to connect individual behavior to collective dynamics. His work has appeared or is forthcoming in Nature Scientific Reports, the American Sociological Review, the American Journal of Sociology, Social Networks, Social Forces, Advances in Group Processes and Frontiers in Cognitive Psychology, among others.

Aaron Clauset | University of Colorado Boulder
Aaron Clauset is an Assistant Professor in the Department of Computer Science and the BioFrontiers Institute, and is External Faculty at the Santa Fe Institute. Prof. Clauset is an internationally recognized expert on network science, computational social, and machine learning for complex systems. His work has appeared in many prestigious scientific venues and in the popular press. He received a PhD in Computer Science from the University of New Mexico, a BS in Physics from Haverford College and was an Omidyar Fellow at the Santa Fe Institute.

Paul Davis | RAND
Paul K. Davis is a Principal Researcher and a Professor of Policy Analysis in the Pardee RAND Graduate School. His research areas include strategic planning, deterrence theory, decision science, cognitive modeling, heterogeneous information fusion, and advanced methods of modeling and analysis, to include causal social-science modeling. Dr. Davis has published well over 200 books, reports, and papers. Before joining RAND he was a senior executive is the Office of the Secretary of Defense. He holds a bachelor’s degree from the University of Michigan and a Ph.D. in theoretical chemical physics from MIT.

Michael Gabbay | University of Washington
Michael Gabbay is a Senior Principal Physicist in the UW Applied Physics Laboratory. His current research involves the development and application of mathematical models and computational simulations of network dynamics, focusing on social and political systems. He has conducted empirical research using political rhetoric, human subjects experiments, and analyst input and has applied his models and methods towards understanding and anticipating the behavior of real-world militant networks and government leadership groups. He received his B.A. in Physics from Cornell University and Ph.D. in Physics from the University of Chicago.

Randall Lewis | Netflix
Randall Lewis is an Economic Research Scientist in the Science & Algorithms team where he combines machine learning and econometrics to develop scalable causal measurement and prediction systems that help humans and machine-learning algorithms make optimal choices. Prior to joining Netflix in 2015, he worked at Google and Yahoo! Research where he studied advertising’s impact on human behavior and sought ways to improve the health and efficiency of digital markets. Randall earned his PhD in economics from MIT. Earlier, graduated from BYU as a valedictorian with a double major in economics and mathematics.

Jalal Mahmud | IBM
Jalal Mahmud is a Research Scientist and Manager at IBM Almaden Research Center. His research interests include Computational User Modeling, Intelligent User Interface, Web Analytics, Social Media Analysis, Machine Learning and Data Mining. He led the research for several IBM Watson products such as personality insights, tone analyzer and emotion modeling. Jalal received MS and Ph.D. in Computer Science from Stony Brook University in 2006 and 2008, respectively. He is a member of the IBM Academy of Technology and a senior member of ACM. You can learn more at his IBM Research Web page and his personal website.

Haile Owusu | Mashable
Haile Owusu is Chief Data Scientist at Mashable where his main responsibility is the development and refinement of the company's proprietary Velocity technology, which predicts and tracks the viral life-cycle of digital media content. Prior to joining Mashable Haile led all research efforts for SocialFlow, one of the leading social media optimization platforms for leading brands and publishers. Haile specializes in statistical learning as applied to predictive analytics and has a background in theoretical physics, including a Ph.D from Rutgers University, a Masters of Science from King's College, University of London and a B.A. from Yale University.

Sharon C Roberts | University of Massachusetts Amherst
Dr. Shannon C. Roberts is an Assistant Professor in the Mechanical and Industrial Engineering Department. Dr. Roberts' education and research focus have been centered on studying and evaluating the interaction between humans and systems, with particular attention paid to transportation safety. She has authored 12 publications in referred journals, conference proceedings, and technical reports. She also serves as a reviewer for numerous conferences and journalsShe received her B.S. degree in Mechanical Engineering from MIT and her Masters and Ph.D. in Industrial Engineering from the University of Wisconsin Madison.

Amy Sliva | Charles River Analytics
Amy Sliva is a Senior Scientist at Charles River Analytics focusing on interdisciplinary research that combines artificial intelligence and social science models to support decision making. Before joining Charles River Analytics, Dr. Sliva was an Assistant Professor of Computer Science and Political Science at Northeastern University. Dr. Sliva received her Ph.D. in Computer Science from the University of Maryland. She also has a B.S. in Computer Science from Georgetown University, an M.S. in Computer Science from the University of Maryland, and a Master of Public Policy in International Security and Economic Policy from the University of Maryland.

Lisa Singh | Georgetown
Dr. Lisa Singh is Professor in the Computer Science Department. She has authored/co-authored over 50 peer reviewed publications and book chapters. Her research has been supported by NSF, ONR, DARPA, and SSHRC. Among other projects, she is currently studying privacy on the web and learning from open source big data for social science research related to public opinion, election dynamics, and child behavior. She received her B.S.E. from Duke University and her M.S. and Ph.D. from Northwestern University.

Michael Wu | Lithium
Dr. Michael Wu is the Chief Scientist at Lithium, where he currently applies data-driven methodologies to investigate and understand the social web. Michael has developed many predictive social analytics with actionable insights. His R&D work has won him the recognition as a 2010 Influential Leader by CRM Magazine. Prior to industry, Michael received his Ph.D. from UC Berkeley’s Biophysics program, where he also received his triple major undergraduate degree in Applied Math, Physics, and Molecular & Cell Biology.