Session 1 – The Future of Voting
The role of technology in voting has gained increasing prominence over the past decade, creating interdisciplinary collaborations between political, computer, and data scientists. Voting data contains an abundance of information that goes beyond the actual vote. This session will look at the complexity of voting, the usability of computing technologies (such as cryptography) in designing future voting systems, and how data is playing a role in understanding and predicting voting patterns and the outcome of elections.
Professor Munther Dahleh, Director of IDSS
Messina Group Analytics
Session 2 – Data Driven Policy
While communities are collecting more data than ever before to measure effects of public policy, such data sets tend to be quite small. With the absence of a control group, the assessment of existing policies and the design of new ones utilizing such data bring new challenges to statistics and data science. This panel will explore such challenges and will highlight how data analysis has been quite effective in some applications.
University of Rome Tor Vergata
Session 3 – Risk in Financial Systems
Recent research has been successful in deriving abstracted models of the interconnected financial systems that quantify systemic risk and address cascaded failures of such systems. However, combining such models with recorded data for the purpose of monitoring and mitigation continues to be a major research and practical challenge. This session will discuss such challenges, as well as the progress that has been made.
Session 4 – Social Networks
Social networks through social media have brought to bear very large data representing people’s preferences and opinions, and have highlighted effective incentive mechanisms. Such networks also impact and inform a variety of complex systems in our society. Such data has brought in new security and privacy challenges that have occupied much of the research in data science. This panel will look at new opportunities for understanding social networks and human behavior, as well as technological methods for ensuring security and privacy.
Dean of the School of Engineering, MIT
Session 5 – Future Electric Grid
The electric grid presents some of the most challenging engineering, social, and economic challenges of the future. With increased demands on electricity and increased penetration of renewable sources, the need for new innovations in dynamic demand response, spot markets, and distributed control is rapidly increasing. This session will discuss some of these challenges and current work.
Session 6 – Student Session
Session 7 – Analyzing our Health
The collection, aggregation, and analysis of medical data presents possibilities for future healthcare developments, including opportunities for personalized medicine and patient care. The use of big data in medicine also raises serious questions about patient privacy. This session will discuss ways in which the practice of medicine is being transformed by data.
Dean of the School of Humanities, Arts, and Social Sciences, MIT
Beth Israel Deaconess Medical Center
Professor of Medicine at Harvard Medical School of Medicine (HMS) and
MIT Health Sciences and Technology Program (HST)
Session 8 – Driving Smart Cities Forward
Cities will become increasingly interconnected through an ever-expanding “internet of things,” allowing governments, urban planners and engineers access to massive amounts of data about urban life. This data is being used to design, plan, and structure cities in the United States and around the world. This session seeks to explore the many facets of smart-cities research, design, planning, and transportation.
Session 9 – From Applications to Theory
While applications have their own nuances, there are overarching challenges that need to be identified and addressed. These include, among others, fundamental questions in prediction, robustness/risk, computation, system architecture, and privacy. This session will address some of the emerging challenges in these foundational fields in this new era of large data and complex systems.
Université catholique de Louvain