Privacy@Michigan 2020

Sol Bermann is the Executive Director of Information Assurance and Chief Information Security Officer for the University of Michigan. Appointed to the role in June 2019, Sol is responsible for the university's information assurance (IT security, privacy, IT policy, compliance, and enterprise continuity) program, including Ann Arbor, Flint, Dearborn, and the Health System.

Since joining the university in 2011, Sol has served as the University Privacy Officer, and IT Policy and Compliance Strategist. In this role he has, among other things, provided strategic direction in how the institution engages cloud services; implemented the policy on the use of personally owned devices when working with sensitive data,; coordinated efforts related to securing sensitive research data, university data governance, and the development of proposed learning analytics guiding principles; and development of the university’s Sensitive Data Guide to IT Services. He served as Interim Chief Information Security Officer during the 2014/15 and 2017/19 academic years.

Prior to joining U-M, Sol was the Director of International Privacy at Walmart, and previous to that was Chief Privacy Officer for the State of Ohio. He began his career as Operations Manager of the Technology Policy Group, a non-profit organization affiliated with the Ohio SuperComputer Center and The Ohio State University. He later served as Associate Director of the Center for Interdisciplinary Law and Policy Studies at The Ohio State University Moritz College of Law, and was adjunct faculty in Ohio State’s International Studies Program.

Sol is active in the EDUCAUSE Higher Education Chief Privacy Officer Working Group, where he served as co-chair through 2016, and was a member of the EDUCAUSE Higher Education Information Security Council. He has written numerous publications, including co-authoring “Information Privacy: Official Reference for the Certified Information Privacy Professional.” He also has presented on privacy, IT policy and information security at numerous conferences, workshops and forums.

Sol holds a B.A from Beloit College, a M.A. from the University of Virginia, and a J.D. from the The Ohio State University Moritz College of Law. He is married and lives in Ann Arbor. He is an artist, primarily working in mixed media and photography, and loves the wide variety of cultural offerings the university and the city provide.

Sandvig is a faculty member at the School of Information specializing in information infrastructure and social media. His current work focuses on the implications of algorithmic systems that filter and curate culture. Before moving to Michigan, Sandvig taught at the University of Illinois at Urbana-Champaign and Oxford University. Sandvig's research has been covered by The Economist, The New York Times, Le Monde, National Public Radio, CBS News, and other media outlets. His own writing appears in Wired and The Guardian. His work has been funded by the National Science Foundation, the MacArthur Foundation, and the Social Science Research Council. He has consulted for Intel, Microsoft, and the San Francisco Public Library.

Paul Resnick is the Michael D. Cohen Collegiate Professor of Information and Associate Dean for Research and Faculty Affairs at the University of Michigan School of Information. He previously worked as a researcher at AT&T Labs and AT&T Bell Labs, and as an Assistant Professor at the MIT Sloan School of Management. He received the master's and Ph.D. degrees in Electrical Engineering and Computer Science from MIT, and a bachelor's degree in mathematics from the University of Michigan.

Professor Resnick's research focuses on SocioTechnical Capital, productive social relations that are enabled by the ongoing use of information and communication technology. His current projects include nudging people toward politically balanced news consumption and health behavior change, and crowdsourcing rumor tracking and fact-correction on the Internet.

Resnick was a pioneer in the field of recommender systems (sometimes called collaborative filtering). Recommender systems guide people to interesting materials based on recommendations from other people. The GroupLens system he helped develop was awarded the 2010 ACM Software Systems Award. His articles have appeared in Scientific American, Wired, Communications of the ACM, The American Economic Review, Management Science, and many other venues. His 2012 MIT Press book (co-authored with Robert Kraut), was titled “Building Successful Online Communities: Evidence-based Social Design”.

H. V. Jagadish is Bernard A Galler Collegiate Professor of Electrical Engineering and Computer Science at the University of Michigan in Ann Arbor. Prior to 1999, he was Head of the Database Research Department at AT&T Labs, Florham Park, NJ.

Professor Jagadish is well known for his broad-ranging research on information management, and has approximately 200 major papers and 37 patents. He is a fellow of the ACM, “The First Society in Computing,” (since 2003) and serves on the board of the Computing Research Association (since 2009). He has been an Associate Editor for the ACM Transactions on Database Systems (1992-1995), Program Chair of the ACM SIGMOD annual conference (1996), Program Chair of the ISMB conference (2005), a trustee of the VLDB (Very Large DataBase) foundation (2004-2009), Founding Editor-in-Chief of the Proceedings of the VLDB Endowment (2008-2014), and Program Chair of the VLDB Conference (2014).Ê Since 2016, he is Editor of the Morgan & Claypool Synthesis Lecture Series on Data Management. Among his many awards, he won the ACM SIGMOD Contributions Award in 2013 and the David E Liddle Research Excellence Award (at the University of Michigan) in 2008.

Sara Rampazzi is a Research Investigator at the Electrical Engineering and Computer Science Department at the University of Michigan. She holds a Ph.D. from the University of Pavia (Italy). Rampazzi’s research focuses on hardware security, in particular on defending cyber-physical systems and their sensors against hardware-based vulnerabilities. In her last project, she discovers how to inject inaudible and invisible commands to smart home devices, such as Amazon Alexa and Google Home. Rampazzi's research has been covered by CNN, The New York Times, Ars Technica, Wired, ABC and NBC News, and other media outlets.

In her research, she also tackles the fundamental challenges necessary to protect health information systems from signal injection attacks and aims to redefine fundamental hardware-software interactions to allow autonomous transportation systems to remain reliable despite untrustworthy data from sensors and hardware components. Besides co-supervising graduate and undergraduate students, Rampazzi is also an intermittent lecturer in the EECS department.