2024 Future Leaders Summit
Time and Location: April 8-10, 2024 on the University of Michigan Ann Arbor campus.
Theme: “Responsible data science and AI.”
More Event InformationFaculty Mentors
Brittany Aguilar
Science Associate
Schmidt Sciences
Elizabeth Bondi-Kelly
Visiting Assistant Professor of Electrical Engineering and Computer Science, College of Engineering
University of Michigan
Bill Currie
Associate Dean, Research and Engagement, Professor of Environment and Sustainability, School for Environment and Sustainability
Jamal El-Hindi
Former U.S. Treasury Financial Crimes Enforcement Network (FinCEN) Deputy Director
Clifford Chance
Arya Farahi
Assistant Professor, Dept of Statistics and Data Science
University of Texas, Austin
Kent Foster
Director, Innovation + Society
Microsoft
R. Stuart Geiger
Assistant Professor, Dept of Communication and the Halıcıoğlu Data Science Institute
Affiliate Faculty, Institute for Practical Ethics,
Computer Science & Engineering, and Computational Social Science,
University of California, San Diego
Min Kyung Lee
Assistant Professor, School of Information
University of Texas, Austin
Michael Tjalve
Chief AI Architect, Tech for Social Impact at Microsoft Philanthropies
Assistant Professor, Linguistics
University of Washington
Elizabeth Yakel
Olivia Frost Collegiate Professor of Information, School of Information;
Faculty Associate, Inter-University Consortium for Political and Social Research, Institute for Social Research
University of Michigan
The 2024 Future Leaders Summit is sponsored by
2023 Future Leaders Summit
Time and Location: April 12-14, 2023 on the University of Michigan Ann Arbor campus.
Theme: “Responsible data science and AI.”
More Event InformationFaculty Mentors
Tanya Berger-Wolf
Director of the Translational Data Analytics Institute,
The Ohio State University
Andrew J. Connolly
Visiting Assistant Professor of Electrical Engineering and Computer Science, College of Engineering
University of Michigan
H. V. Jagadish
Professor of Computer Science and Engineering, MIDAS Director
University of Michigan
Mark Moldwin
Professor, Climate and Space Sciences and Engineering
University of Michigan
Josh Pasek
Associate Professor of Communication and Media & Political Science, MIDAS Associate Director,
University of Michigan
Ellie Sakhaee
Office of Responsible AI
Microsoft
The 2023 Future Leaders Summit is sponsored by
Microsoft
Rocket Companies
2022 Future Leaders Summit
Time and Location: April 6-7, 2022 on the University of Michigan Ann Arbor campus.
Theme: “Responsible data science and AI.”
Article: MIDAS Future Leaders Summit highlights Responsible Data Science and AI
More Event InformationFaculty Mentors
H. V. Jagadish
Professor of Computer Science and Engineering, MIDAS Director
University of Michigan
Frauke Kreuter
Professor of Survey Methodology, Director of Social Data Science Center
University of Maryland
David Mongeau
Director, School of Data Science
Professor of Practice
University of Texas at San Antonio
Shashi Shekhar
Professor of Computer Science
University of Minnesota
Michael Wellman
Professor and Chair of Computer Science and Engineering
University of Michigan
The 2022 Future Leaders Summit is sponsored by
Michigan DEI Office
Microsoft
Rocket Companies
2020 Data Science Consortium
The 2020 cohort comes from 28 universities, and will meet virtually on Oct. 29th-30th to participate in research talk presentations, networking sessions, and mentoring opportunities.
The research talk presentations will take place from 12:00pm – 2:00pm EST each day and are open to the public.
Mentoring session speakers:
- Dr. Jeffrey Fessler, Professor of the Department of Electrical and Computer Engineering, University of Michigan
- Dr. Margaret Levenstein, Director of the Inter-university Consortium for Political and Social Research, University of Michigan
- Dr. Kevin Ward, Professor of Emergency Medicine, University of Michigan
- Dr. Michael Wellman, Professor and Chair of the Department of Computer Science and Engineering, University of Michigan
- Dr. Marybeth Broadbent, Data Scientist at Google
October 30th Schedule
12:00pm – 12:10pm: Opening remarks, Jing Liu (Managing Director, MIDAS) [Join via Zoom]
Presentations
Data Science and the Physical World [Join via Zoom]
Time | Name | University | Title of Presentation |
12:10pm – 12:25pm | Karianne Bergen | Harvard University | Shaking up Earthquake Science in the Age of Big Data |
12:25pm – 12:40pm | Roshan Kulkarni | Iowa State University | Modeling for ambiguous SNP calls in allotetraploids |
12:40pm – 12:55pm | Chris Powell | Oakland University | PATS: a taxon re-sampling pipeline to test phylogenetic stability in large datasets |
12:55pm – 1:10pm | Sameer | Penn State University | Unveiling the nature of the Circumgalactic medium |
1:10pm – 1:25pm | Yan Li | University of Minnesota | Physics-guided Energy-efficient Path Selection |
1:25pm – 1:40pm | Elham Taghizadeh | Wayne State University | Framework for Effective Resilience Assessment of Deep-Tier Automotive Supply Networks |
Data Science and Human Society [Join via Zoom]
Time | Name | University | Title of Presentation |
12:10pm – 12:25pm | Aviv Landau | Columbia University | Artificial Intelligence-Assisted Identification of Child Abuse and Neglect in Hospital Settings with Implications for Bias Reduction and Future Interventions |
12:25pm – 12:40pm | Thibaut Horel | Massachusetts Institute of Technology | The Contagiousness of Police Violence |
12:40pm – 12:55pm | Chris Ick | New York University | Robust Sound Event Detection in Urban Environments |
12:55pm – 1:10pm | Renhao Cui | Ohio State University | Restricted Paraphrase Generation Model for Commercial Tweets |
1:10pm – 1:25pm | Rezvanah Rezapour | University of Illinois at Urbana-Champaign | Text Mining for Social Good; Context-aware Measurement of Social Impact and Effects Using Natural Language Processing |
October 30th Schedule
12:00pm – 12:10pm: Welcome back, Jing Liu (Managing Director, MIDAS) [Join via Zoom]
Presentations
Data Science Theory and Methodology [Join via Zoom]
Time | Name | University | Title of Presentation |
12:10pm – 12:25pm | Paidamoyo Chapfuwa | Duke University | Bringing modern machine learning to survival analysis |
12:25pm – 12:40pm | Heakyu Park | Georgia Institute of Technology | Bluff: Interactive Interpretation of Adversarial Attacks on Deep Learning |
12:40pm – 12:55pm | Tanima Chaterjee | University of Illinois at Chicago | On the Computational Complexities of Three Privacy Measures for Large Networks Under Active Attack |
12:55pm – 1:10pm | Behnaz Moradi | University of Virginia | Introducing retraced non-backtracking random walk (RNBRW) as a tool to uncover the mesoscopic structure of open-source software (OSS) networks |
1:10pm – 1:25pm | Sanjeev Kaushik | Florida International University | Securing the IoT Communication |
1:25pm – 1:40pm | Arya Farahi | University of Michigan | Towards Trustworthy and Fair Classifiers |
1:40pm – 1:55pm | Qi Zhao | University of California, San Diego | Persistence Enhanced Graph Neural Network |
Data Science and Human Health [Join via Zoom]
Time | Name | University | Title of Presentation |
12:10pm – 12:25pm | Sarah Ben Mamaar | Northwestern University | Comprehensive analysis of the reproducibility of RNAseq computational pipelines |
12:25pm – 12:40pm | Váleri Vásquez | University of California, Berkeley | Optimizing Genetic-Based Public Health Interventions |
12:40pm – 12:55pm | Abby Stevens | University of Chicago | Modeling the Impact of Social Determinants of Health on COVID-19 Transmission and Mortality to Understand Health Inequities |
12:55pm – 1:10pm | Sean Kent | University of Wisconsin | Multiple Instance Learning from Distributional Instances |
1:10pm – 1:25pm | LaKeithia Glover | Clark Atlanta University | Suicide Rates on African African Youth as it relates to the Influence of Different types of Communication |
1:35-1:40pm | Matt Satusky | University of North Carolina at Chapel Hill | BioData Catalyst and Deep Learning: Feature extraction on a full-feature platform |
1:40pm – 1:55pm | Juandalyn Burke | University of Washington | Using an Ecological Inference Software Tool to Detect Vote Dilution |
Other Attendees
Name | University |
Sandrine Muller | Columbia University |
Jonathan Proctor | Harvard University |
Etienne Nzabarushimana | Indiana University |
Kate Mortensen | Indiana University |
Zhouhan Chen | New York University |
Ashley Superson | Oakland University |
Alex Aguilar | Rice University |
Adam Anderson | University of California, Berkeley |
Like Hui | University of California, San Diego |
Elena Graetz | University of Illinois at Chicago |
Jayant Gupta | University of Minnesota |
Aji John | University of Washington |
The 2020 Data Science Consortium is sponsored by
Google Cloud
2019 Data Science Consortium
Name | University | Department | Abstract Title |
Dhivya Eswaran | Carnegie Mellon University | Computer Science | “SedanSpot: Detecting Anomalies in Edge Streams” |
Otilia Stretcu | Carnegie Mellon University | Machine Learning | “Graph Agreement Models for Semi-Supervised Learning” |
William Dula | Clark Atlanta University | Mathematical Sciences | “Application of a Contour Theory Method to Load Profiling in a Power Utility” |
Ipek Ensar | Columbia University | Data Science Institute | “Exercise as medicine: Can exercise behavior predict endometriosis disease symptom severity?” |
Sandrine Muller | Columbia University | Data Science Institute | “Everyday Mobility Behaviors Predict Psychological Well-Being Among Young Adults” |
Marko Angjelichinoski | Duke University | Electrical and Computer Engineering | “Robust Estimation and Classification for Brain-Computer Interfaces” |
Didong Li | Duke University | Mathematics | “Density Estimation on Manifolds with Fisher-Gaussian Kernels” |
Robert Ravier | Duke University | Electrical Engineering | “Foundational Issues in Computational Evolutionary Biology and Political Science” |
Shan Shan | Duke University | Mathematics | “Probabilistic Models on Fibre Bundles” |
Daniel Ruiz-Perez | Florida International University | Computing and Information Sciences | “Predicting microbe-microbe interactions from time series metagenomic data” |
Thinh Doan | Georgia Institute of Technology | Electrical and Computer Engineering & Industrial and Systems Engineering | “Distributed Decision Making on Multi-Agent Systems” |
Michelle Ntampaka | Harvard University | Harvard Data Science Initiative | “A Deep Learning Approach to Galaxy Cluster X-ray Masses” |
Dakota Murray | Indiana University Bloomington | Informatics | “Making sense of scientific systems” |
Lanmiao He | Iowa State University | Psychology | “Being aware helps: how mindfulness and data analytics benefit students and an educational NPO” |
Gianina Alin Negoita | Iowa State University | Animal Science | “Face2Face: Facial Expression Transfer” |
Tuhin Sarkar | Massachusetts Institute of Technology | Electrical Engineering | “Learning Structure from Unstructured Data” |
Anastasios Noulas | New York University | Center for Data Science | “Wiki-Atlas: Rendering Wikipedia Content through Cartographic and Augmented Reality Mediums” |
Nan Wu | New York University | Center for Data Science | “Towards solving breast cancer screening diagnosis with deep learning” |
Asmamaw Gebrehiwot | North Carolina A&T State University | Applied Science and Technology | “Flood Extent Mapping using Unmanned Aerial Vehicle Imagery” |
Luiz G. A. Alves | Northwestern University | Chemical & Biological Engineering | “Reconstructing commuters network using machine learning and urban indicators” |
Yian Yin | Northwestern University | Industrial Engineering and Management Science | “Quantifying dynamics of failure across science, startups, and security” |
Lige Gan | Oakland University | Computer Science and Engineering | “Attention-based Multi-Source Representation Learning” |
Arunima Srivastava | The Ohio State University | Computer Science and Engineering | “Interpretable and Context Based Neural Network Modeling of Histology Images” |
Andrew Polasky | Penn State | Meteorology and Atmospheric Science | “Statistical Downscaling of Climate Models using self-organizing maps” |
Yi-Yu Lai | Purdue University | Computer Science | “Relational Representation Learning Incorporating Textual Communication for Social Networks” |
Ye Emma Zohner | Rice University | Statistics | “Bayesian Functional Regression on Manifold via Spherical Wavelets” |
Baharan Mirzasoleiman | Stanford University | Computer Science | “Large-scale Combinatorial Optimization for Data Summarization and Resource-efficient Machine Learning” |
Stuart Geiger | UC-Berkeley | Berkeley Institute for Data Science | “Operationalizing Conflict and Cooperation Between Automated Software Agents in Wikipedia: A Replication, Refutation, and Expansion of ‘Even Good Bots Fight.’” |
Yang Junwen | University of Chicago | Computer Science | “Improving Performance and Quality of Database-Backed Software” |
Yushen Dong | University of Illinois at Chicago | Mathematics, Statistics, and Computer Science | “Nonparametric interaction selection for additive model” |
Oluwagbemiga Ajayi | University of Maryland Baltimore County | Information Systems | “Diagnosis Of Type II Diabetes Using Machine Learning Techniques” |
Ronak Razavisousan | University of Maryland Baltimore County | Information Systems | “Two Layer Clustering Analysis of Student Migration from Twitter Posts” |
Srinivas Rallapalli | University of Minnesota | Bioproducts and Biosystems Engineering | “Developing an optimized decision support framework for sustainable field-scale assessment by integrating ACPF, PTMApp, and HSPF-SAM” |
Tony Cannistra | University of Washington | Biology | “Data Science Methods and Climate Change Ecology: A Scientific Imperative” |
Erin Wilson | University of Washington | Computer Science and Engineering | “Using microorganisms to solve macro problems: untangling the genetic circuitry of methane-eating bacteria” |
Mina Karzand | UW Madison | Wisconsin Institute for Discovery | “Active Learning in the Overparameterized and Interpolating Regime” |
Najibesadat Sadati | Wayne State University | Industrial and Systems Engineering | “Dynamic Resource Allocation for Coordination of Inpatient Operations in Hospitals” |