rayid ghani

Rayid Ghani is the Director of the Center for Data Science & Public Policy and a Senior Fellow at the Harris School of Public Policy and the Computation Institute at the University of Chicago. Rayid is a reformed computer scientist and wanna-be social scientist, but mostly just wants to increase the use of data-driven approaches in solving large public policy and social challenges. Among other areas, Rayid works with governments and non-profits in policy areas such as health, criminal justice, education, public safety, economic development, and urban infrastructure. Rayid is also passionate about teaching practical data science and started the Eric & Wendy Schmidt Data Science for Social Good Fellowship at UChicago that trains computer scientists, statisticians, and social scientists from around the world to work on data science problems with social impact. Rayid also teaches data science and machine learning class at Harris and is actively involved in the joint Computer Science and Public Policy Masters program at the University of Chicago.

Before joining the University of Chicago, Rayid was the Chief Scientist of the Obama 2012 Election Campaign where he focused on data, analytics, and technology to target and influence voters, donors, and volunteers. Previously, Rayid was a Research Scientist and led the Machine Learning group at Accenture Labs. Rayid did his graduate work in Machine Learning at Carnegie Mellon University and is actively involved in organizing Data Science related conferences and workshops. In his ample free time, Rayid works with non-profits to help them with their data, analytics and digital efforts and strategy.

A longer profile and publications can be found at http://www.rayidghani.com

Frauke Kreuter

Frauke Kreuter is Professor in the Joint Program in Survey Methodology at the University of Maryland, Professor of Methods and Statistics at the University of Mannheim, and head of the statistical methods group at the German Institute for Employment Research in Nuremberg. Previously she held positions in the Department of Statistics at the University of California Los Angeles (UCLA), and the Department of Statistics at the Ludwig-Maximillian’s University of Munich. Frauke Kreuter serves on several advisory boards for National Statistical Institutes around the world, and within the Federal Statistical System in the United States. She recently served as the co-chair of the Big Data Task force of the American Association for Public Opinion Research. Frauke Kreuter is a Gertrude Cox Award winner, recognizing statisticians in early- to mid-career who have made significant breakthroughs in statistical practice, and an elected a fellow of the American Statistical Association. Her textbooks on Data Analysis Using Stata, and Practical Tools for Designing and Weighting Survey Samples, are used at universities world-wide, and her Massive Open Online Course in Questionnaire Design attracted over 70.000 learners within the first year. Recently Frauke Kreuter launched the international long distance professional education program sponsored by the German Federal Ministry of Education and Research in Survey and Data Science.

Julia Lane

Julia Lane is a Professor at the NYU Wagner Graduate School of Public Service, at the NYU Center for Urban Science and Progress, and a NYU Provostial Fellow for Innovation Analytics.

Previous to this, Julia was a Senior Managing Economist and Institute Fellow at American Institutes for Research. In this role Julia established the Center for Science of Science and Innovation Policy Program, and co-founded the Institute for Research on Innovation and Science (IRIS) at the University of Michigan. Julia has held positions at the National Science Foundation, The Urban Institute, The World Bank, American University and NORC at the University at Chicago. 

In these positions, Julia has led many initiatives, including co-founding the UMETRICS and STAR METRICS programs at the National Science Foundation. She conceptualized and established a data enclave at NORC/University of Chicago. This provides a confidential, protected environment within which authorized researchers canaccess sensitive microdata remotely and provides data producers with a secure disseminationplatform. She also initiated and led the creation and permanent establishment of the Longitudinal Employer-Household Dynamics Program at the U.S. Census Bureau. This program began as a small two year ASA Census Bureau fellowship and evolved into the first large-scale linked employer-employee dataset in the United States. It is now a permanent Census Bureau program with appropriated funds of $11 million per year.

Julia has published over 70 articles in leading economics journals, and authored or edited ten books. She is an elected fellow of the American Association for the Advancement of Science and a fellow of the American Statistical Assocation.  She has been the recipient of over $50 million in grants; from foundations such as the National Science Foundation, the Alfred P. Sloan Foundation, the Ewing Marion Kauffman Foundation, the MacArthur Foundation, the Russell Sage Foundation, the Spencer Foundation, the National Institutes of Health; from government agencies such as the Departments of Commerce, Labor, and Health and Human Services in the U.S., the ESRC in the U.K., and the Department of Labour and Statistics New Zealand in New Zealand, as well as from international organizations such as the World Bank. Julia is the recipient of the 2014 Julius Shiskin award and the 2014 Roger Herriot award.

Julia received her PhD in Economics and Master's in Statistics from the University of Missouri.

Julia Koschinsky

Julia Koschinsky is the Research Director of the Center for Spatial Data Science at the University of Chicago and has been part of Luc's team for over ten years. She has been conducting and managing research funded through federal awards of over $8 million to gain insights from the spatial dimensions of urban challenges in housing, health, and the built environment.

JAMES LYNCH

James Lynch is professor and chair of the Department of Criminology and Criminal Justice at the University of Maryland. Lynch joined the department after serving as the director of the Bureau of Justice Statistics (BJS) in the United States Department of Justice. Previously, he was a distinguished professor in the Department of Criminal Justice at John Jay College, City University of New York. He was a professor in the Department of Justice, Law and Society at American University from 1986 to 2005 and chair of that department from 2003 to 2005. Lynch's research focuses on victim surveys, victimization risk, the role of coercion in social control, and crime statistics. He has published four books and numerous articles many of them dealing with crime statistics.   He was vice president-elect of the American Society of Criminology (ASC) and served on the Committee on Law and Justice Statistics of the American Statistical Association. From 2008 to 2010 he was co-editor of the Journal of Quantitative Criminology.  Lynch received his B.A. degree from Wesleyan University and his M.A. and Ph.D. in sociology from the University of Chicago.

Jeri Mulrow

Jeri Mulrow in January joined the U.S. Bureau of Justice Statistics as principal deputy director. Prior to taking the new position, Mulrow served the National Center for Science and Engineering Statistics (NCSES) at the National Science Foundation where she was deputy division director. She has 30 years of experience as an applied statistician working in government, industry and academia, and has worked at the National Institute of Standards and Technology (NIST), Southern Illinois University, the Statistics of Income Division at the Internal Revenue Service (IRS), NORC at the University of Chicago and Ernst & Young, LLP. Mulrow is a fellow of the American Statistical Association (ASA) and is currently serving a three-year elected term as vice president of ASA. She holds a bachelor’s degree in mathematics from Montana State University and a master’s degree in statistics from Colorado State University.

Steven Rich

Steven Rich is the database editor for the investigations unit at The Washington Post. While at The Post, he’s worked on investigations involving the NSA, police shootings, tax liens, civil forfeiture and college athletics. He was a reporter on the team awarded the 2014 Pulitzer Prize for Public Service for NSA revelations. He was also a reporter on the team to win the 2016 Pulitzer Prize for National Reporting for a database and series on fatal shootings by police nationwide. Rich is a graduate of Virginia Tech and the University of Missouri and is originally from Collegeville, Pa.

alex engler

Alex Engler is a data scientist working to apply statistical methods, data visualizations, and big-data analytics for public policy research. He developed Urban Institute's approach to massive data statistical analysis and is a principal investigator on a grant to improve on and disseminate that approach to other social scientists. In addition, he acts as the statistical and computational lead on an ambitious endeavor to generate synthetic administrative datasets. 

Outside his role at the Urban Institute, Engler teaches courses on data visualization and data science in public policy at Johns Hopkins University and Georgetown University. He recently developed and enacted a new graduate degree program in Data Science and Public Policy at Georgetown University.

kristine rogers

Kristine served as a manager on a digital data analysis team, with the primary focus on setting a technology strategy for rapid identification of useful information of large datasets. She is cofounder and leader of multiple affinity groups relating to networking, technology, and analytic tradecraft. Her past experience includes management and analytic positions on big data analysis, technology policies and priorities, and cyber threat analysis.

thomas j. herzog

A 32 year veteran of Corrections and Parole work, Mr. Herzog is the President and Chief Executive Officer of Tom Herzog Consulting, and The Herzog Group, organizations that provide technology and policy advice to Corrections, Community Supervision and Law Enforcement organizations.

Mr. Herzog retired in July 2015 as the Deputy Commissioner for the New York State Department of Corrections and Community Supervision where he was responsible for all matters related to the Department’s Community Supervision Division, as well as its Technology, Strategic Planning and Research functions.

Mr. Herzog’s many accomplishments include the development of a new and exciting community supervision model in 2014 known as RESET – Recidivism Elimination and Supervision Enhancement Teams which will greatly enhance the Department’s success rate of parolees by introducing modern scientific principles to the supervision process.

Mr. Herzog was the architect of the Department’s SMART initiative – Security Management Assessment Response Team in 2014, an empirically based model that utilizes advanced analytical techniques to identify the causes of prison violence and innovative strategies to reduce inmate assaults.

Mr. Herzog led New York State’s effort in 2013-14 to secure over $20 million in government and private sector funding to establish Pay For Success, the largest Social Impact Bond effort in the world at that time. Private sector funds from Merrill Lynch and Bank of America are used to fund a program designed to reduce parolee recidivism by increasing employment opportunities for newly released offenders.

Mr. Herzog is a past President of the Corrections Technology Association;  20 of his 32 years of public safety experience include a concentration in Corrections and Public Safety Technology. He is the former Chief Information Officer of both the New York State Parole Division and the New York State Department of Correctional Services where he championed and led many technological and operational innovations. 

Ravi Shroff

Ravi Shroff is a Senior Research Scientist at New York University’s Center for Urban Science and Progress (CUSP), where he specializes in computational social science. His work involves using statistical and machine learning techniques to understand the criminal justice system, child welfare, and related urban issues.  He studied mathematics at UC San Diego (PhD) and applied urban science and informatics at CUSP (MS).

greg stoddard

I’m a data scientist at the University of Chicago Crime Lab (but working in their New York City office). I recently completed my PhD in computer science at Northwestern University, where I was advised by Dr. Nicole Immorlica.

My current work at the Crime Lab is applies the best practices and techniques of social science and machine learning to help cities address policy problems. You can read more about our work here.

My graduate research was about understanding and optimizing the behavior of large socio-technical systems, with a particular emphasis on economic incentives, via data science. I’m also generally interested in developing principled approaches for evaluating counterfactual predictions in data science applications.

In my spare time I play lots of hockey (both ice and roller). I would abandon data science immediately if the New York Rangers would give me some fourth line minutes. I infrequently tweet about data science and/or hockey at @gregstod.

Daniela Hochfellner

Daniela Hochfellner is a Senior Research Scientist and Research Assistant Professor at at the NYU Center for Urban Science and Progress. She also is an Adjunct Research Assistant Professor at the Institute for Social Research, Survey Research Center at the University of Michigan. Previous to this, Daniela was a Research Investigator at the Institute for Social Research, Survey Research Center at the University of Michigan and a Researcher at the Research Data Centre at the Institute for Employment Research in Nuremberg, Germany. She received her PhD in Sociology from the University of Bamberg (in Germany). 

Her research addresses the economics of labor markets, migration, aging and health and ethics in human subject research. Daniela pursues research on labor market participation of older workers, and effects of social security reforms on retirement transition and health outcomes. Her work on research ethics addresses data confidentiality and methods of protecting privacy in the presence of an increasing demand of “big data” in social sciences.

She has worked with survey data, administrative data, and big-data and has a deep knowledge and extensive experience in linkages of social security records, administrative information and survey data. She implements statistically grounded approaches to data integration, data use and dissemination of policies and procedures.

jonathan morgan

In his position as Senior Research Scientist, Jon works with the CUSP Data Facility team and their collaborators on the Census Bureau Prototype Data Facility project. He also works with the Data Facility team to design and implement secure, reliable and scalable software services in addition to enhancing the full software development life cycle.

Prior to joining CUSP, Jon was a Systems Architect at NIE Online Inc. and a Systems Integration Manager at IData Inc. where he served as a systems architect, designer and technical team lead for complex higher education system integration projects. Jon has also worked as an instructor at Michigan State University and as a Technology and Process Consultant for nationwide news organizations.

Jon has a Master of Arts in Journalism degree from New York University and is in the process of completing his PhD studies at Michigan State University (MSU) as a University Enrichment Fellow, which is MSU’s most prestigious graduate fellowship. In addition to his vast technical experience and programming skills, Jon continues to teach on varied class topics such as scalable computational science and journalism history.

Timothy H. Savage

Timothy Savage is the Senior Managing Economist for Econometric Advisors, where he assists leadership in EA’s strategy, daily operations and client-facing engagement. He also assists on special projects, such as examining the potential impacts of automation on property use and using the tools of machine learning to identify suburban clusters that function similarly to central business districts.

Dr. Savage is an econometrician with more than 15 years of experience in economics and business consulting at international firms such as Charles River Associates and Navigant Consulting. Since the global financial crisis, he has focused on financial econometrics, simulation modeling, and examining conditions under which causal inferences can be drawn from non-experimental data. Dr. Savage’s published works range from assessing adverse labor market outcomes’ implications for the career paths of younger workers to evaluating the impact of pollution on residential property values. Dr. Savage has also developed survey instruments and data analysis to examine consumers’ willingness to pay for improvements in air quality.

Dr. Savage has been featured in PWC’s “Cities of Opportunity,” and his research has been discussed in The Economist. He has addressed the National League of Cities on the uses of big data in policymaking. He is a visiting scholar and adjunct professor at New York University’s Center for Urban Science and Progress.  He holds a Ph.D. in economics from the University of North Carolina—Chapel Hill.

John C. Havens

John C. Havens is Executive Director of The IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems. The Initiative created a document called, Ethically Aligned Design to provide recommendations for values-driven Artificial Intelligence and Autonomous Systems as well standards recommendations. Guided by over one hundred thought leaders, The Initiative has a mission of ensuring every technologist is educated, trained, and empowered to prioritize ethical considerations in the design and development of autonomous and intelligent systems.

John is also a regular contributor on issues of technology and wellbeing to Mashable, The Guardian, HuffPo and TechCrunch and is author of Heartificial Intelligence: Embracing Our Humanity To Maximize Machines and Hacking Happiness: Why Your Personal Data Counts and How Tracking it Can Change the World.

John was an EVP of a Top Ten PR Firm, a VP of a tech startup, and an independent consultant where he has worked with clients such as Gillette, P&G, HP, Wal-Mart, Ford, Allstate, Monster, Gallo Wines, and Merck.  He was also the Founder of The Happathon Project, a non-profit utilizing emerging technology and positive psychology to increase human wellbeing.

John has spoken at TEDx, at SXSW Interactive (six times), and as a global keynote speaker for clients like Cisco, Gillette, IEEE, and NXP Semiconductors.  John was also a professional actor on Broadway, TV and Film for fifteen years. 

For more information, visit John’s site or follow him @johnchavens.

BEN SHNEIDERMAN

BEN SHNEIDERMAN (http://www.cs.umd.edu/~ben) is a Distinguished University Professor in the Department of Computer Science and Founding Director (1983-2000) of the Human-Computer Interaction Laboratory (http://www.cs.umd.edu/hcil/) at the University of Maryland.  He is a Fellow of the AAAS, ACM, and IEEE, and a Member of the National Academy of Engineering, in recognition of his pioneering contributions to human-computer interaction and information visualization. His contributions include the direct manipulation concept, clickable web-link, touchscreen keyboards, dynamic query sliders for Spotfire, development of treemaps, innovative network visualization strategies for NodeXL, and temporal event sequence analysis for electronic health records.

Ben is the co-author with Catherine Plaisant of Designing the User Interface: Strategies for Effective Human-Computer Interaction (5th ed., 2010) http://www.awl.com/DTUI/.  With Stu Card and Jock Mackinlay, he co-authored Readings in Information Visualization: Using Vision to Think (1999).  His book Leonardo’s Laptop appeared in October 2002 (MIT Press) and won the IEEE book award for Distinguished Literary Contribution.  His latest book, with Derek Hansen and Marc Smith, is Analyzing Social Media Networks with NodeXL (www.codeplex.com/nodexl, 2010).