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Coffee and Check-In
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Opening Remarks
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Triage Score: A Counterfactual Risk Assessment Instrument

Kosuke Imai (Harvard University)
Video
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Operational Dosage: The Impact of Capacity Constraints on RCT Evaluation

Hannah Li (Columbia University)
Video
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Break
–
LLM-Guided Reinforcement Learning for Mastery Learning: Large-Scale Field Evidence

Hamsa Bastani (Upenn)
Video
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Estimating the Value of Personalization

Emma Brunskill (Stanford University)
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Lunch (catered)
–
Non-parametric Causal Inference in Dynamic Thresholding Designs

Stefan Wager (Stanford University)
Video
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Provocations- "Evaluation in the Wild: The Need for Engagement"

Daniel Ho (Stanford University)
–
Provocations

Deirdre Mulligan (UC Berkeley)
–
Panel (In-person only)
–
Reception
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Coffee and Check-In
–
What Birth Circumstances Cannot Predict: Toward a General Framework for Prediction Ceilings (In-person only)

Matthew Salganik (Princeton University)
–
Agreement and Alignment for Human-AI Collaborative Decision Making

Aaron Roth (University of Pennsylvania)
Video
–
Break
–
The Role of Standardized Tests in Admissions: Predictions vs. Decisions

Sharad Goel (Harvard University)
Video
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Individual Gaps in Prediction Generalization

Marzyeh Ghassemi (MIT)
Video
–
Lunch (catered)
–
Human Values in Clinical Algorithms, Old and New

Arjun Kumar Manrai ()
Video
–
Provocations

Mark Sendak
–
Provocations

Jean Feng (UCSF)
–
Provocations

Ziad Obermeyer (UC Berkeley)
–
Provocations- "A Roadmap for Removing Race from Clinical Algorithms"

Emma Pierson (UC Berkeley)
–
Provocations

Benjamin Recht (UC Berkeley)
–
Panel (In-person only)
–
Discussions (In-person only)
–
Coffee and Check-In
–
Beyond Prediction Performance: How Modeling Decisions Shape Fairness Outcomes in Statistical Profiling

Frauke Kreuter (LMU Munich and University of Maryland)
Video
–
The Feedback Loop of Statistical Discrimination

Jackie Baek (NYU Stern)
Video
–
Decision theoretic foundations for human-AI collaboration

Jessica Hullman (Northwestern University)
Video
–
Break
–
When Prediction Becomes Policy: What Do Risk Models Actually Learn?

Shion Guha (University of Toronto)
Video
–
Evaluation Design

Ashia Wilson (MIT)
Video
–
Lunch (on your own)
–
Poster Session (In-person only)
–
Free Afternoon
–
Coffee and Check-In
–
Recommendation in equilibrium for the NYC High School Match

Nikhil Garg (Cornell University)
Video
–
Automating the US Welfare State: Historical Experiments in Technological Federalism

Marc Aidinoff (Harvard University)
Video
–
Evaluating probabilistic decision making by LLMs: a decision-theoretic framework and application to clinical diagnosis

Bryan Wilder (Carnegie Mellon University)
Video
–
Break
–
On Machine Learning for Prediction and Prioritization in the Allocation of Scarce Societal Resources

Sanmay Das (Virginia Tech)
Video
–
Algorithmic UDAP

Talia Gillis (Columbia University)
Video
–
Lunch (catered)
–
Machine Learning Who to Nudge: Causal vs Predictive Targeting in a Field Experiment on Student Financial Aid Renewal

Jann Spiess (Stanford University)
Video
–
The Challenge of Valid Evaluations

Amanda Coston (UC Berkeley)
Video
–
The Inadequacy of Offline LLM Evaluations: A Need to Account for Personalization in Model Behavior

Angelina Wang (Cornell Tech)
Video
–
Informal Discussions (In-person only)
–
Coffee and Check-In
–
Closing Remarks
–
Scheduling with Time-Evolving Uncertainty for Content Review Prioritization in Social Media

Thodoris Lykouris (MIT)
Video
–
Break
–
Provocations

Ashesh Rambachan (MIT)
–
Provocations

Eli Ben Michael (Carnegie Mellon University)
–
Provocations

Tijana Zrnic (Stanford University)
–
Limits of Decisions and Inference under Uncertainty Panel
–
Lunch (on your own)
–
Informal Discussions (In-person only)
–
Break
–
Informal Discussions (In-person only)