*Note: These events are being recorded by audio, video, and photographic means. By attending, you grant the University of Virginia the right to use your voice/likeness in any depiction of these events.
Seminar Speaker: Behnaz Moradi
Title: Detecting Communities and Performing Statistical Inferences on Networks through Renewal Non-backtracking Random Walks
Abstract: In many sciences, units under study often share connections and belong to communities, and within the same community, they behave similarly. A critical problem in these sciences is how to identify communities given a mathematical network.
The detection of these communities can be aided through the use of measures of the local "richness" of cyclic structures. In this dissertation, we develop the renewal non-backtracking random walk (RNBRW), a variant of random walk in which the walk is prohibited from returning back to a node in exactly two steps and terminates and restarts once it completes a loop, as a way of quantifying this cyclic structure. Specifically, we propose using the retracing probability of an edge, the likelihood that the edge completes a cycle in RNBRW, as a way of quantifying cyclic structure.
We conclude by describing connections between RNBRW and the maximum expected cyclic overlap problem and give theoretical results of RNBRW under the stochastic block model.
Bio: Behnaz Moradi earned her Master of Science and Bachelor of Science in Industrial Engineering from Amir Kabir University of Technology. She earned her Ph.D. in Statistics from Kansas State University in August 2019. She is currently working as a Postdoctoral Associate Researcher at the School of Data Science and is a member of the Computational System Biology Lab within the Department of Biomedical Engineering at the University of Virginia.
Date: February 7, 2020
Time: 10:30 - 11:30 AM
Location: Biocomplexity Institute
1100 Wilson Boulevard, Suite 2910
Arlington, VA 22209
Introduction to the Julia Language
Learn about the Julia language: the basics, why it is so great, and how we use it as a tool for data science for the public good in our work. We will showcase some of the great features Julia offers, key projects in the ecosystem, its community, and how to apply it to various applications. This session will give brief presentations on how to use Julia for reproducible research, regular expressions, REST/GraphQL API, I/O, tabular data, databases, and regression analysis.
Date: January 16, 2020
Time: 3:30 - 5:00 PM
Location: Biocomplexity Institute
1100 Wilson Boulevard, Suite 2910
Arlington, VA 22209
Data Science for the Public Good Forum
The Biocomplexity Institute is launching the Data Science for the Public Good Forum!
The DSPG Forum is comprised of a Distinguished Speaker Series and Annual Symposium. These events bring together key public and private stakeholders to discuss how “doing data science” can support evidence-based policymaking and innovation to enhance the quality of life where we all live, learn, work, and play.
Learn more about each program and register for the events on our DSPG Forum page.
Past Events
Datapalooza 2019 with Keynote Speaker Sallie Keller
November 1, 2019
Doing Data Science in Service of the Public Good
Dr. Keller is Director of the Social and Decision Analytics Division within the Biocomplexity Institute and Initiative at University of Virginia and a Professor of Public Health Sciences. She spoke at the fifth anniversary of Datapalooza, an event hosted by UVA's Data Science Institute. To watch her keynote speech at Datapalooza, click here and fast forward to 5:05.
Colloquium: Saikou Diallo
September 23, 2019
We're Are All in It Together: Training the Next Generation of Model Thinkers
In this talk, Dr. Saikou Diallo discusses transdisciplinarity, inclusion, and social awareness as three pillars that we can build on to stay relevant in a world where technological change is outpacing our ability to manage and predict its impact on key aspects of life and society. He presented tools, models and practical examples to illustrate the importance of each pillar and provide a basis for what we hope is a strong debate within the scientific community.
Data Science for the Public Good Distinguished Speaker Series
September 17, 2019
Informing Decisions while Protecting Privacy: The Future of the Federal Statistical System
Katharine Abraham is the Director of the Maryland Center for Economics and Policy, and a professor of Survey Methodology and Economics at the University of Maryland. In her talk, Dr. Abraham spoke of different ways to address the challenges currently facing the Federal statistical system, including: the use of naturally-occurring "big data", new models, and strengthened partnerships with academia and businesses.
Colloquium: Ian Davidson
September 13, 2019
Towards Explainable Clustering (X-Clustering)
Ian Davidson is a Professor of Computer Science at the University of California Davis. This talk was based on joint research with colleagues and students from the Biocomplexity Institute and Initiative of the University of Virginia, University of California Davis, Google Research, University de Lyon (France), and University de Orleans (France).
Data Science for the Public Good Annual Symposium
August 9, 2019
The Data Science for the Public Good Annual Symposium is a showcase for researchers across the country, including the Institute's DSPG Young Scholars. This year's Symposium featured keynote speakers Phil Bourne, director of the University of Virginia’s Data Science Institute and acting dean of the School of Data Science, and Ron Jarmin, deputy director and chief operating officer of the U.S. Census Bureau.
Computing for Global Challenges Symposium
July 29, 2019
The symposium showcased the Network Systems Science and Advanced Computing division's summer students and their research projects. Student projects covered a range of topics, including bacterial quorum sensing, RNA sequence analysis, flu forecasting, transportation modeling, and disaster resilience, among others.
Data Science for the Public Good Distinguished Speaker Series
June 14, 2019
Smart Government: The Data, the Map, and the Method.
The former Governor of Maryland, Martin O'Malley, kicked off the Data Science for the Public Good Distinguished Speaker Series with his talk, Smart Government: The Data, the Map, and the Method, emphasizing the need for more evidence-based policy making.
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