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.

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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.

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Nick Feamster is Neubauer Professor in the Department of Computer Science and the College and the Faculty Director of Research for the Data Science Institute. 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.

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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.

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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.

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.

Dr. Jeanne Century is the Director of Outlier Research & Evaluation and a Research Associate Professor. Century’s work has almost exclusively focused on advancing equity in education primarily through research-practice partnership arrangements in large and small urban school districts. During her 35-year career (including 17 at UChicago STEM Education at the University of Chicago) Century been the principal investigator of numerous federal and foundation research grants focusing on a range of topics including inquiry science instruction, computer science education, STEM schools and sustainability of reform. Century’s primary research focus is on understanding, measuring, and supporting education innovation implementation, spread and endurance through implementation science and component-based approaches. Century has also conducted numerous evaluations on out-of-school and in-school programs, district and state reform efforts, higher education, teacher preparation, and civic leadership. In addition to research, Century has developed instructional materials, supported professional learning efforts for teachers and administrators and has provided technical assistance and strategic planning for leaders at the school, district, and state levels. Century also has policy experience at all education system levels including serving on the Obama-Biden transition team where she was responsible for STEM education as well as the Department of Education Agency Review.

Aloni Cohen is an Assistant Professor of Computer Science and Data Science at the University of Chicago. Previously, Cohen was a Postdoctoral Associate at Boston University, with a joint appointment at the Hariri Institute for Computing and the School of Law. His research explores the interplay between theoretical cryptography, privacy, law, and policy. Aloni earned his PhD in electrical engineering and computer science at MIT where he was advised by Shafi Goldwasser and supported by a Facebook Fellowship and an NSF Graduate Student Fellowship. Aloni is a former affiliate at the Berkman Klein Center for Internet & Society and a Fellow at the Aspen Tech Policy Hub.

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. Right now, I’m thinking about differential privacy, GDPR, the Fifth Amendment, encryption, multiparty computation, and the Census.

Greg Green is Senior Instructional Professor and Director of the MScA Program at the University of Chicago, and Senior Director for Industrial Partnerships and Strategy at the Data Science Institute. 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.

Alex Kale is an Assistant Professor in Computer Science and the Data Science Institute at the University of Chicago. Previously, he earned his PhD at the University of Washington where he worked with Jessica Hullman. Alex leads the Data Cognition Lab, focused on creating data visualization and analysis software that explicitly represents the user’s cognitive processes.

Alex creates and evaluates tools for helping people think with data, specializing in data visualization and reasoning with uncertainty. He publishes in top human-computer interaction and data visualization venues such as ACM CHI and IEEE VIS, where his work has won Best Paper and Honorable Mention Awards. Alex’s work addresses gaps in dominant theories and models of what makes visualization effective for inferences and decision making.

Kristian was named a National Academy of Science Kavli Fellow this past year. She was also recognized by the Committee of Presidents of Statistical Societies with the Emerging Leader in Statistics Award (2022). She is a founding member of the Executive Committee of ACM conference on Fairness, Accountability, and Transparency (FAccT) — the premier venue for work on the societal impacts of algorithmic systems. Kristian brings a unique and critically valuable research experience across academic, nonprofit and industry settings. Most recently she was a Senior Staff Machine Learning Researcher on the ML Ethics, Transparency and Accountability Team at Twitter. Prior to taking a role in industry, she held academic positions including as an Assistant Research Professor at the University of Pennsylvania, Department of Computer and Information Science and as an Assistant Research Professor at Virginia Tech. Kristian has also served as the Lead Statistician for the Human Rights Data Analysis Group where she advised New York City’s Mayor’s Office of Criminal Justice and Philadelphia’s First Judicial District on how to create algorithmic tools that better embody notions of fairness.

Amy Nussbaum joined the University of Chicago in Fall 2022. She holds a PhD in Statistical Sciences from Southern Methodist University, where she researched latent variables—those that cannot be measured directly, like happiness or stress. Specifically, she studies the assessment of personality traits. Most recently, she held the position of Visiting Lecturer of Statistics at Mount Holyoke College.

In addition to academia and research, she encourages understanding the use of statistics in government and industry. After graduation, she served as the inaugural Science Policy Fellow at the American Statistical Association, working to promote the practice and profession of statistics by advocating for evidence-based policy making and the federal statistical agencies, as well the lead statistician for a medical device company developing a novel imager able to detect diseased human tissue using artificial intelligence.

Nick Ross is an experienced data science executive with significant leadership experience in both industry and academic settings. Nick has successfully built and managed data science teams at companies ranging from small startups to multinational corporations, and he continues to advise organizations on all things data and engineering.  Before joining The University of Chicago, he led the data science and backend engineering teams at an e-sports startup based in San Francisco.

Academically, Nick was most recently an Assistant Professor of Data Science at The University of San Francisco (USF). In addition to his to teaching and research duties, Nick was the Director of USF’s Data Science Practicum Program and oversaw industry outreach and partnerships for USF’s newly formed Data Institute.

Nick is a proud product of the University of California system, having received his undergraduate degree in Math from  UC Berkeley, his Masters in Economics from UC Davis, and his Ph.D. from UCLA’s Anderson School of Management.

Aaron is an Assistant Professor in the Statistics Department and Data Science Institute at UChicago. His research develops methodology in Bayesian statistics, causal inference, and machine learning for applied problems in political science, economics, and genetics, among other fields. Prior to joining UChicago, Aaron was a postdoctoral fellow in the Data Science Institute at Columbia University. He received his PhD in Computer Science from UMass Amherst, as well as an MA in Linguistics and a BA in Political Science. He is on Twitter @AaronSchein.

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.

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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.

Haifeng Xu is an assistant professor in the Department of Computer Science and the Data Science Institute at UChicago. He directs the Strategic IntelliGence for Machine Agents (SIGMA) research lab which focuses on designing algorithms/systems that can effectively elicit, process and exploit information, particularly in strategic environments. Haifeng has published more than 55 publications at leading venues on computational economics, machine learning and theoretical computer science, such as EC, ICML, NeurIPS, STOC and SODA. His research has been recognized by multiple awards, including the Google Faculty Research Award, ACM SIGecom Dissertation Award (honorable mention), IFAAMAS Victor Lesser Distinguished Dissertation Award (runner-up), Google PhD fellowship, and multiple best paper awards.

The following research themes are the recent focus of our research lab. Please refer to our lab’s website for more details.

• The economics of data/information, including selling, acquiring, and exploiting information
• Machine learning in multi-agent setups under information asymmetry, incentive conflicts, and deception
• Resource allocation in adversarial domains, with applications to security and privacy protection

Evelyn  is a preceptor in data science focusing on data science education as a joint instructor for both the University of Chicago and City Colleges of Chicago. She obtained her PhD in Microbiology from the University of Chicago in 2022 and her BS in Biology from Rider University in 2016. She enjoys reading, writing, and talking with friends and family.

Amanda is a preceptor in data science focusing on data science education as a joint instructor for both the University of Chicago and City Colleges of Chicago. Prior to joining the DSI, Amanda earned her PhD in Computational and Data Sciences from Washington University in St. Louis, co-advised by Sanmay Das and Patrick Fowler. Her research interests involve the intersection of computer science and the social sciences with a focus on fair applications of AI to social-scientific questions. Her current work combines machine learning and human decision-making to inform fair and efficient service allocations for homeless families. She received her bachelor’s degree in Psychology and Statistics and her master’s degree in Data Analytics and Statistics both from Washington University in St. Louis.

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.

Nzinga-Ain Barberousse was homeschooled until college and remains engaged in the Chicagoland homeschooling community. She earned a Bachelor’s degree in Neuroscience from UIC and a Master’s degree in Clinical Psychology – Counseling Practice from Roosevelt University, where she graduated magna cum laude. Nzinga has experience in projects and program management, including work as a LPC-eligible Adolescent Therapist (focusing on trauma, mood, and substance use), experience as a Legal Project Manager, and time as the Piano Program Director for the Hyde Park Suzuki Institute.

Nzinga is a passionate animal lover, particularly of reptiles and rodents, and has special interest in neuropsychology, especially in the areas of Autism and ADHD. In her free time, she teaches private piano lessons, enjoys reading, embroidery, and baking, as well as trying new restaurants, learning new languages, and traveling to new places. Nzinga values collaboration and open communication and is a team player, always looking for new opportunities to learn and grow, both professionally and personally.

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.

Tim Hannifan is Assistant Clinic Director for the Data Science Institute at the University of Chicago. He is responsible for managing the execution of an experiential learning program for University students, recruiting and retaining data science partner organizations, and mentoring student teams to implement data science solutions for government, industry, and social impact organizations. Prior to joining the DSI, Tim worked on data science initiatives at Mathematica Policy Research and The World Bank. He holds a MS in Computational Analysis and Public Policy and a BA in Economics from the University of Chicago.

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

https://github.com/jesteria

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.

Susan Paykin leads management of the Open Spatial Lab’s programmatic, technical research, and engagement activities at DSI. In this role she is also thrilled to help oversee the Community Data Fellows program, cultivating impactful collaborations between students and Chicago-area civic and social impact organizations. Susan has an extensive background in strategic program development and geospatial data analysis and project management, most recently as the Research Manager at the Center for Spatial Data Science and Healthy Regions and Policies Lab at UChicago. She holds a Master’s in Public Policy from the Harris School of Public Policy at University of Chicago and a B.A. in International and Global Studies from Brandeis University.

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.

Stephen Baker is Senior Evaluation & Research Scientist at Outlier Research & Evaluation and a mixed-methods researcher who has conducted program and policy evaluations for over thirty years. He has served as panel reviewer for NSF and the Department of Education and principal investigator and project director on evaluations funded by local and national philanthropic foundations, the Department of Education and NSF. His evaluation and research portfolio is broad, with concentrations in education reform, informal learning, community-based and collaborative policy approaches, and the social and emotional bases of student success. His current projects include a Department of Education RCT assessing STEM career development in high school students; a UChicago and City Colleges of Chicago collaboration to increase international content in CCC courses; an implementation study of evidence-based interventions at the Illinois Department of Children and Family Services; and an NSF “Harnessing the Data Revolution” effort to develop convergent instruction materials for CyberGIS.

He holds masters’ and doctoral degrees from the Crown Family School and was a researcher at Chapin Hall at UChicago for more than 20 years. He has taught graduate and undergraduate courses at the University in evaluation, research, data management, and U.S. social welfare. He was a member of the University of Chicago SSA/Chapin Hall Institutional Review Board, Crown Family School field instructor, and serves as facilitator of the Mansueto Institute for Urban Innovation Doctoral Fellows program.

Joanna Schiffman is a Lead Research & Evaluation Associate at Outlier and is interested in examining how cognitive processes, attitudes, experiences, and environmental factors impact STEM learning. Since joining Outlier Research & Evaluation in 2019, Joanna has worked on a variety of research projects, including a Department of Education EIR-funded project examining the impact of STEM career readiness and social-emotional learning programming on urban high school students’ interest in pursuing STEM careers. Joanna has also carried out evaluations of educational programs with UChicago internal departments and organizations, including the Area Studies Center and the Network for College Success (NCS), as well as external organizations, including ComEd SmartGrid STEM Programs, Chicago Learning Exchange (CLX), and MathTalk.

Prior to joining Outlier, Joanna’s research focused on the factors that influence young children’s math and spatial learning, including parental input and interaction, environmental contexts, and additional cognitive factors. Her dissertation examined the role of metacognition in children’s arithmetic strategy selection, and her previous research position, at Susan Levine’s Cognitive Development lab in University of Chicago’s Psychology department, included studies of children’s spatial cognition, supported by the NSF-funded Spatial Intelligence and Learning Center. In addition, Joanna has taught psychology and education courses at the undergraduate level, and developed a fully virtual course for all incoming Master of Education Students at Harvard Graduate School of Education appropriately called How People Learn.

Joanna earned her Ph.D. in Applied Developmental and Educational Psychology at Boston College Lynch School of Education & Human Development and a B.A. in Psychology with a Cognitive Science concentration from Wesleyan University.

Dr. Huifang Zuo is a Research and Evaluation Associate in Outlier Research & Evaluation at the University of Chicago since 2017. She received her Doctoral Degree in Educational Research Methodology (focusing on quantitative methods) and M.A. in Geography Information Science (GIS). Currently, she is studying interdisciplinary quantitative methods that can be applied in educational research through the Master program of Quantitative Methods & Social Analysis at the University of Chicago. Dr. Huifang Zuo specializes in STEM education and workforce development research, particularly for underserved K12 populations. She also conducted geography-related educational research with integrating GIS technologies into education to better explore and understand educational outcomes. During her professional training, her research has focused on STEM education, neighborhood conditions in relation to academic achievement, and self-efficacy in learning English as a second language.