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Michael J. Franklin is the inaugural holder of the Liew Family Chair of Computer Science. An authority on databases, data analytics, data management and distributed systems, he also serves as senior advisor to the provost on computation and data science.

Previously, Franklin was the Thomas M. Siebel Professor of Computer Science and chair of the Computer Science Division of the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. There, he co-founded Berkeley’s Algorithms, Machines and People Laboratory (AMPLab), a leading academic big data analytics research center. The AMPLab won a National Science Foundation CISE “Expeditions in Computing” award, which was announced as part of the White House Big Data Research initiative in March 2012, and received support from over 30 industrial sponsors. AMPLab created industry-changing open source Big Data software including Apache Spark and BDAS, the Berkeley Data Analytics Stack. At Berkeley, he also served as an executive committee member for the Berkeley Institute for Data Science, a campus-wide initiative to advance data science environments.

An energetic entrepreneur in addition to his academic work, Franklin founded and became chief technology officer of Truviso, a data analytics company acquired by Cisco Systems. He serves on the technical advisory boards of various data-driven technology companies and organizations.

Franklin is a Fellow of the Association for Computing Machinery and a two-time recipient of the ACM SIGMOD (Special Interest Group on Management of Data) “Test of Time” award. His many other honors include the outstanding advisor award from Berkeley’s Computer Science Graduate Student Association. He received the Ph.D. in Computer Science from the University of Wisconsin in 1993, a Master of Software Engineering from the Wang Institute of Graduate Studies in 1986, and the B.S. in Computer and Information Science from the University of Massachusetts in 1983.


Dan Nicolae obtained his Ph.D. in statistics from The University of Chicago and has been a faculty at the same institution since 1999, with appointments in Statistics (since 1999) and Medicine (since 2006). His research focus is on developing statistical and computational methods for understanding the human genetic variation and its influence on the risk for complex traits, with an emphasis on asthma related phenotypes. The current focus in his statistical genetics research is centered on data integration and system-level approaches using large datasets that include clinical and environmental data as well as various genetics/genomics data types: DNA variation, gene expression (RNA-seq), methylation and microbiome.


Nick Feamster is Neubauer Professor in the Department of Computer Science and the College. He researches computer networking and networked systems, with a particular interest in Internet censorship, privacy, and the Internet of Things. His work on experimental networked systems and security aims to make networks easier to manage, more secure, and more available.


Rebecca Willett is a Professor of Statistics and Computer Science at the University of Chicago. She completed her PhD in Electrical and Computer Engineering at Rice University in 2005 and was an Assistant then tenured Associate Professor of Electrical and Computer Engineering at Duke University from 2005 to 2013. She was an Associate Professor of Electrical and Computer Engineering, Harvey D. Spangler Faculty Scholar, and Fellow of the Wisconsin Institutes for Discovery at the University of Wisconsin-Madison from 2013 to 2018.  Prof. Willett received the National Science Foundation CAREER Award in 2007, was a member of the DARPA Computer Science Study Group 2007-2011, and received an Air Force Office of Scientific Research Young Investigator Program award in 2010. Prof. Willett has also held visiting researcher positions at the Institute for Pure and Applied Mathematics at UCLA in 2004, the University of Wisconsin-Madison 2003-2005, the French National Institute for Research in Computer Science and Control (INRIA) in 2003, and the Applied Science Research and Development Laboratory at GE Medical Systems (now GE Healthcare) in 2002. Her research interests include network and imaging science with applications in medical imaging, wireless sensor networks, astronomy, and social networks. She is also an instructor for FEMMES (Females Excelling More in Math Engineering and Science; news article here) and a local exhibit leader for Sally Ride Festivals. She was a recipient of the National Science Foundation Graduate Research Fellowship, the Rice University Presidential Scholarship, the Society of Women Engineers Caterpillar Scholarship, and the Angier B. Duke Memorial Scholarship.


David Uminsky joined the University of Chicago in September 2020 as a senior research associate and Executive Director of Data Science. He was previously an associate professor of Mathematics and Executive Director of the Data Institute at University of San Francisco (USF). His research interests are in machine learning, signal processing, pattern formation, and dynamical systems.  David is an associate editor of the Harvard Data Science Review.  He was selected in 2015 by the National Academy of Sciences as a Kavli Frontiers of Science Fellow. He is also the founding Director of the BS in Data Science at USF and served as Director of the MS in Data Science program from 2014-2019. During the summer of 2018, David served as the Director of Research for the Mathematical Science Research Institute Undergrad Program on the topic of Mathematical Data Science.

Before joining USF he was a combined NSF and UC President’s Fellow at UCLA, where he was awarded the Chancellor’s Award for outstanding postdoctoral research. He holds a Ph.D. in Mathematics from Boston University and a BS in Mathematics from Harvey Mudd College.

Julia Lane is the Executive Director for Research Partnerships & Strategy, responsible for shaping and executing the strategic vision of DSI, building new research partnerships and outreach strategies to foster interdisciplinary collaborations, and ensuring that the University continues to broaden applications of data science and computing approaches.

Mindi has experience managing, sourcing and scoping a portfolio of data science experiential learning partnerships across social impact organizations, corporate, civic and government entities. Mindi managed earlier iterations of our work with the 11th Hour Project at the University of San Francisco where she served as the Senior Director of Strategy and Operations of the Data Institute. Mindi is a member (inactive) of the California and Illinois bars and received her JD from UC Hastings and her BS, Political Science from Santa Clara University.


I’m a Postdoctoral Associate at the Hariri Institute for Computing at Boston University and the Boston University School of Law. I’ll be joining the University of Chicago as an Assistant Professor of Computer Science and Data Science starting January 2022.

My research explores the interplay between theoretical cryptography, privacy, law, and policy. Specifically, I aim to understand and resolve the tensions between the theory of cryptography and the privacy and surveillance law that governs its eventual real-world context. I earned my PhD in the Cryptography and Information Security group at MIT, advised by Shafi Goldwasser. Right now, I’m thinking about differential privacy, GDPR, the Fifth Amendment, encryption, multiparty computation, and the Census. Formerly an Affiliate at the Berkman Klein Center for Internet & Society, a Fellow at Facebook and at the Aspen Tech Policy Hub, and recipient of the NSF Graduate Student Research Fellowship.

Greg Green is the Senior Instructional Professor and Director of the MScA Program at the University of Chicago, within the Data Science Institute of the Physical Sciences Division. Dr. Green helps the University of Chicago professional data science students learn to apply data science to solve complex industry problems with greater impact.

Dr. Green is reshaping the content and approaches used to educate the next generation of professional data scientists at the University of Chicago.  Additionally, Greg is designing new, creative offerings more deeply connected to MS and PhD research programs in Data Science, Computer Science, Statistics, and Financial Mathematics. New course offerings developed launched since joining the University of Chicago include an innovative approach to “Leadership in Data Science and Artificial Intelligence”, “Consulting in Data Science” and “Your Career in Data Science”.

Throughout his professional career, Greg has used his expertise in digital strategies, business analytics, and new product development to drive rapid revenue growth and accelerate business transformation. His previous work bringing innovation to an academic environment included authoring a Marketing Analytics course, designing a pre-requisite applied statistics course and serving as a lecturer for Marketing Analytics at Northwestern University.

Greg’s industry roles include Chief Analytics Officer at Harland Clarke Holdings, Director at Google, EVP/Managing Director at Publicis Groupe, and Analytics Practice Lead at PwC. Greg’s patented cloud-based media analytics platform was highlighted in Harvard Business Review and Fast Company.

Greg holds a Doctor of Philosophy in Mathematics from Claremont Graduate School and a Master of Science in Statistics from Michigan State University. Born in Owosso, Michigan, Greg is married to Jill, an artist, and their adult children include two more artists, a teacher, and an engineer. Greg and his family enjoy snowboarding, snow/water skiing and live theatre—as well as good food and friendships. Their passion for the environment is reflected in a love for Lake Michigan where they like to spend as much of the summer as possible.

Chenhao Tan is an assistant professor at the Department of Computer Science and the UChicago Data Science Institute. His main research interests include language and social dynamics, human-centered machine learning, and multi-community engagement. He is also broadly interested in computational social science, natural language processing, and artificial intelligence.


I am an assistant professor of Statistics and Data Science at the University of Chicago and a research scientist at Google Cambridge. My recent work revolves around the intersection of machine learning and causal inference, as well as the design and evaluation of safe and credible AI systems. Other noteable areas of interests include network data, and the foundations of learning and statistical inference.

I was previously a Distinguished Postdoctoral Researcher in the department of statistics at Columbia University, where I worked with the groups of David Blei and Peter Orbanz. I completed my Ph.D. in statistics at the University of Toronto, where I was advised by Daniel Roy. In a previous life, I worked on quantum computing at the University of Waterloo. I won a number of awards, including the Pierre Robillard award for best statistics thesis in Canada.


Admin Staff

Rob Mitchum is Associate Director of Communications for Data Science and Computing at the University of Chicago, covering research and faculty for the Department of Computer Science, the Data Science Institute, and other computational initiatives.

Katie Rosengarten is Program Manager at the Data Science Institute, responsible for overseeing strategic partnerships, management, execution, and evaluation of student research engagement opportunities for early high school learners through PhD students.

Technical Staff

Grace Chu is a Community Project Manager supporting the Internet Access & Equity Initiative at the University of Chicago. She helps to build relationships with City and neighborhood-based partners to integrate research and community collaboration.

Launa is a software engineer responsible for executing Data Clinic projects with student teams in conjunction with the 11th Hour Project, as well as internal projects for the DSI. She received her bachelor’s degree in the humanities at Princeton University and her master’s degree in Computational Analysis and Public Policy at the University of Chicago. Prior to joining the University, she worked as an adult education instructor and then as a software consultant at a Microsoft partner company.

Daniel Grzenda is a Staff Data Scientist supporting the partnership with the 11th Hour Project at the University. He engages with social impact organizations across the domains of energy, food and agriculture, human rights, and marine technology, to support applications of data and computer science. Daniel’s work is focused on increasing the data capacity of these organizations, lowering the barriers to mission driven data science, and empowering these organizations through the development of sustainable technical solutions.

Jesse London is a software engineer at the Center for Data and Computing, where he contributes to the CDAC Open-Source Initiative.

Guilherme Martins is the Senior Programming Specialist at CDAC. Guilherme has contributed to critical research projects bringing an extensive domain knowledge expertise acquired over his years in the industry and academia. His skillset includes embedded software development for specialized hardware, data engineering, and software automation.  Most recently, he developed a method for summarizing network traffic utilization while retaining critical information of over-the-top consumer internet applications such as Netflix, Youtube, Amazon, and Facebook. With fine-grain information about their internet utilization, internet consumers are now empowered to make data-driven decisions regarding their home internet infrastructure. The design and implementation of the software allow extensibility and open an interface to new applications ranging from performance monitoring to network security. He’ll be working closely with Nick Feamster and other Principal Investigators to establish data analysis pipelines.

Marc is the technical project manager for the Internet Access and Equity Initiative. He is responsible for working with our researchers and engineers on building the measurement tools and public-facing portal as well as overseeing the In-Home Internet Study. Marc recently graduated from the UChicago CAPP program, and prior to that he was a project manager at a DC-based economic consulting company.

Trevor is an 11th Hour Software Engineer with the DSI. He works with social impact organizations on implementing data science projects that further their mission. Additionally, Trevor mentors student teams for the Civic Data and Technology Clinic. Before the DSI, Trevor worked with computational materials science at Argonne National Laboratory and received his BS from MIT.