Sotabase

Career

· Assistant Professor, Machine Learning Department, Carnegie Mellon University2022–
· Postdoctoral Associate, Machine Learning Department, Carnegie Mellon University2021–2022
· Research Fellow, Center for Communicable Disease Dynamics, Harvard T. H. Chan School of Public Health2021–2022
· PhD in Computer Science, Harvard University2019–2021
· Research Intern, Microsoft Research, Redmond2019–
· PhD Candidate, Department of Computer Science, University of Southern California2015–2019
· B.S. Computer Science, University of Central Florida2011–2015

Publications (146)

Test sensitivity is secondary to frequency and turnaround time for COVID-19 screening
Science Advances · 2020
760
cited
Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization
AAAI Conference on Artificial Intelligence · 2018
352
cited
Test sensitivity is secondary to frequency and turnaround time for COVID-19 surveillance
medRxiv · 2020
307
cited
SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver
International Conference on Machine Learning · 2019
286
cited
End-to-End Constrained Optimization Learning: A Survey
International Joint Conference on Artificial Intelligence · 2021
232
cited
Learning to Complement Humans
International Joint Conference on Artificial Intelligence · 2020
186
cited
MIPaaL: Mixed Integer Program as a Layer
AAAI Conference on Artificial Intelligence · 2019
167
cited
End to end learning and optimization on graphs
Neural Information Processing Systems · 2019
119
cited
Group-Fairness in Influence Maximization
International Joint Conference on Artificial Intelligence · 2019
116
cited
Controlling Elections through Social Influence
Adaptive Agents and Multi-Agent Systems · 2017
68
cited
Maximizing Influence in an Unknown Social Network
AAAI Conference on Artificial Intelligence · 2018
68
cited
Designing Fair, Efficient, and Interpretable Policies for Prioritizing Homeless Youth for Housing Resources
Integration of AI and OR Techniques in Constraint Programming · 2018
63
cited
Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data
Knowledge Discovery and Data Mining · 2019
60
cited
Exploring Algorithmic Fairness in Robust Graph Covering Problems
Neural Information Processing Systems · 2020
59
cited
Modeling between-population variation in COVID-19 dynamics in Hubei, Lombardy, and New York City
Proceedings of the National Academy of Sciences of the United States of America · 2020
58
cited
Uncharted but not Uninfluenced: Influence Maximization with an Uncertain Network
Adaptive Agents and Multi-Agent Systems · 2017
57
cited
Influence Maximization in the Field: The Arduous Journey from Emerging to Deployed Application
Adaptive Agents and Multi-Agent Systems · 2017
54
cited
Decision-Focused Learning without Decision-Making: Learning Locally Optimized Decision Losses
Neural Information Processing Systems · 2022
52
cited
End-to-End Influence Maximization in the Field
Adaptive Agents and Multi-Agent Systems · 2018
47
cited
The Role of Age Distribution and Family Structure on COVID-19 Dynamics: A Preliminary Modeling Assessment for Hubei and Lombardy
2020
46
cited
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