Future Leaders Summit

The MIDAS annual Future Leaders Summit offers outstanding graduate students, postdocs, and early-career faculty from around the US the opportunity to engage in research discussions with peers and with research leaders, and receive career mentoring, as they grow to become leaders in data science and artificial intelligence (AI) research.

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.”

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Faculty 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

Microsoft

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.”

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Faculty 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 Information

Faculty 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:

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]

TimeNameUniversityTitle of Presentation
12:10pm – 12:25pmKarianne BergenHarvard UniversityShaking up Earthquake Science in the Age of Big Data
12:25pm – 12:40pmRoshan KulkarniIowa State UniversityModeling for ambiguous SNP calls in allotetraploids
12:40pm – 12:55pmChris PowellOakland UniversityPATS: a taxon re-sampling pipeline to test phylogenetic stability in large datasets
12:55pm – 1:10pmSameer Penn State UniversityUnveiling the nature of the Circumgalactic medium
1:10pm – 1:25pmYan LiUniversity of MinnesotaPhysics-guided Energy-efficient Path Selection
1:25pm – 1:40pmElham TaghizadehWayne State UniversityFramework for Effective Resilience Assessment of Deep-Tier Automotive Supply Networks

Data Science and Human Society [Join via Zoom]

TimeNameUniversityTitle of Presentation
12:10pm – 12:25pmAviv LandauColumbia UniversityArtificial Intelligence-Assisted Identification of Child Abuse and Neglect in Hospital Settings with Implications for Bias Reduction and Future Interventions
12:25pm – 12:40pmThibaut HorelMassachusetts Institute of TechnologyThe Contagiousness of Police Violence
12:40pm – 12:55pmChris IckNew York UniversityRobust Sound Event Detection in Urban Environments
12:55pm – 1:10pmRenhao CuiOhio State UniversityRestricted Paraphrase Generation Model for Commercial Tweets
1:10pm – 1:25pmRezvanah RezapourUniversity of Illinois at Urbana-ChampaignText 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]

TimeNameUniversityTitle of Presentation
12:10pm – 12:25pmPaidamoyo ChapfuwaDuke UniversityBringing modern machine learning to survival analysis
12:25pm – 12:40pmHeakyu ParkGeorgia Institute of TechnologyBluff: Interactive Interpretation of Adversarial Attacks on Deep Learning
12:40pm – 12:55pmTanima ChaterjeeUniversity of Illinois at ChicagoOn the Computational Complexities of Three Privacy Measures for Large Networks Under Active Attack
12:55pm – 1:10pmBehnaz MoradiUniversity of VirginiaIntroducing retraced non-backtracking random walk (RNBRW) as a tool to uncover the mesoscopic structure of open-source software (OSS) networks
1:10pm – 1:25pmSanjeev KaushikFlorida International UniversitySecuring the IoT Communication
1:25pm – 1:40pmArya FarahiUniversity of MichiganTowards Trustworthy and Fair Classifiers
1:40pm – 1:55pmQi ZhaoUniversity of California, San DiegoPersistence Enhanced Graph Neural Network

Data Science and Human Health [Join via Zoom]

TimeNameUniversityTitle of Presentation
12:10pm – 12:25pmSarah Ben MamaarNorthwestern UniversityComprehensive analysis of the reproducibility of RNAseq computational pipelines
12:25pm – 12:40pmVáleri VásquezUniversity of California, BerkeleyOptimizing Genetic-Based Public Health Interventions
12:40pm – 12:55pmAbby StevensUniversity of ChicagoModeling the Impact of Social Determinants of Health on COVID-19 Transmission and Mortality to Understand Health Inequities
12:55pm – 1:10pmSean KentUniversity of WisconsinMultiple Instance Learning from Distributional Instances
1:10pm – 1:25pmLaKeithia GloverClark Atlanta UniversitySuicide Rates on African African Youth as it relates to the Influence of Different types of Communication
1:35-1:40pmMatt SatuskyUniversity of North Carolina at Chapel HillBioData Catalyst and Deep Learning: Feature extraction on a full-feature platform
1:40pm – 1:55pmJuandalyn BurkeUniversity of WashingtonUsing an Ecological Inference Software Tool to Detect Vote Dilution

Other Attendees

NameUniversity
Sandrine MullerColumbia University
Jonathan ProctorHarvard University
Etienne NzabarushimanaIndiana University
Kate MortensenIndiana University
Zhouhan ChenNew York University
Ashley SupersonOakland University
Alex AguilarRice University
Adam AndersonUniversity of California, Berkeley
Like HuiUniversity of California, San Diego
Elena GraetzUniversity of Illinois at Chicago
Jayant GuptaUniversity of Minnesota
Aji JohnUniversity of Washington

The 2020 Data Science Consortium is sponsored by

Google Cloud

2019 Data Science Consortium

NameUniversityDepartmentAbstract Title
Dhivya EswaranCarnegie Mellon UniversityComputer Science“SedanSpot: Detecting Anomalies in Edge Streams”
Otilia StretcuCarnegie Mellon UniversityMachine Learning“Graph Agreement Models for Semi-Supervised Learning”
William DulaClark Atlanta UniversityMathematical Sciences“Application of a Contour Theory Method to Load Profiling in a Power Utility”
Ipek EnsarColumbia UniversityData Science Institute“Exercise as medicine: Can exercise behavior predict endometriosis disease symptom severity?”
Sandrine MullerColumbia UniversityData Science Institute“Everyday Mobility Behaviors Predict Psychological Well-Being Among Young Adults”
Marko AngjelichinoskiDuke UniversityElectrical and Computer Engineering“Robust Estimation and Classification for Brain-Computer Interfaces”
Didong LiDuke UniversityMathematics“Density Estimation on Manifolds with Fisher-Gaussian Kernels”
Robert RavierDuke UniversityElectrical Engineering“Foundational Issues in Computational Evolutionary Biology and Political Science”
Shan ShanDuke UniversityMathematics“Probabilistic Models on Fibre Bundles”
Daniel Ruiz-PerezFlorida International UniversityComputing and Information Sciences“Predicting microbe-microbe interactions from time series metagenomic data”
Thinh DoanGeorgia Institute of TechnologyElectrical and Computer Engineering & Industrial and Systems Engineering“Distributed Decision Making on Multi-Agent Systems”
Michelle NtampakaHarvard UniversityHarvard Data Science Initiative“A Deep Learning Approach to Galaxy Cluster X-ray Masses”
Dakota Murray Indiana University BloomingtonInformatics“Making sense of scientific systems”
Lanmiao HeIowa State UniversityPsychology“Being aware helps: how mindfulness and data analytics benefit students and an educational NPO”
Gianina Alin NegoitaIowa State UniversityAnimal Science“Face2Face: Facial Expression Transfer”
Tuhin SarkarMassachusetts Institute of TechnologyElectrical Engineering“Learning Structure from Unstructured Data”
Anastasios NoulasNew York UniversityCenter for Data Science“Wiki-Atlas: Rendering Wikipedia Content through Cartographic and Augmented Reality Mediums”
Nan WuNew York UniversityCenter for Data Science“Towards solving breast cancer screening diagnosis with deep learning”
Asmamaw GebrehiwotNorth Carolina A&T State UniversityApplied Science and Technology“Flood Extent Mapping using Unmanned Aerial Vehicle Imagery”
Luiz G. A. AlvesNorthwestern UniversityChemical & Biological Engineering“Reconstructing commuters network using machine learning and urban indicators”
Yian YinNorthwestern UniversityIndustrial Engineering and Management Science“Quantifying dynamics of failure across science, startups, and security”
Lige GanOakland UniversityComputer Science and Engineering“Attention-based Multi-Source Representation Learning” 
Arunima SrivastavaThe Ohio State UniversityComputer Science and Engineering“Interpretable and Context Based Neural Network Modeling of Histology Images”
Andrew PolaskyPenn StateMeteorology and Atmospheric Science“Statistical Downscaling of Climate Models using self-organizing maps”
Yi-Yu LaiPurdue UniversityComputer Science“Relational Representation Learning Incorporating Textual Communication for Social Networks”
Ye Emma ZohnerRice UniversityStatistics“Bayesian Functional Regression on Manifold via Spherical Wavelets”
Baharan MirzasoleimanStanford UniversityComputer Science“Large-scale Combinatorial Optimization for Data Summarization and Resource-efficient Machine Learning”
Stuart GeigerUC-BerkeleyBerkeley 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 JunwenUniversity of ChicagoComputer Science“Improving Performance and Quality of Database-Backed Software”
Yushen DongUniversity of Illinois at Chicago Mathematics, Statistics, and Computer Science“Nonparametric interaction selection for additive model”
Oluwagbemiga AjayiUniversity of Maryland Baltimore CountyInformation Systems“Diagnosis Of Type II Diabetes Using Machine Learning Techniques”
Ronak RazavisousanUniversity of Maryland Baltimore CountyInformation Systems“Two Layer Clustering Analysis of Student Migration from Twitter Posts”
Srinivas RallapalliUniversity of MinnesotaBioproducts and Biosystems Engineering“Developing an optimized decision support framework for sustainable field-scale assessment by integrating ACPF, PTMApp, and HSPF-SAM”
Tony CannistraUniversity of WashingtonBiology“Data Science Methods and Climate Change Ecology: A Scientific Imperative”
Erin WilsonUniversity of WashingtonComputer Science and Engineering“Using microorganisms to solve macro problems: untangling the genetic circuitry of methane-eating bacteria”
Mina KarzandUW MadisonWisconsin Institute for Discovery“Active Learning in the Overparameterized and Interpolating Regime”
Najibesadat SadatiWayne State UniversityIndustrial and Systems Engineering“Dynamic Resource Allocation for Coordination of Inpatient Operations in Hospitals”