Societal Considerations and Applications

Program

Data-Driven Decision Processes

Date

Monday, Nov. 7 – Thursday, Nov. 10, 2022

Back to calendar

9 – 9:25 a.m.

Coffee and Check In

9:25 – 9:30 a.m.

Opening Remarks

9:30 – 10:30 a.m.

Privacy-safe Measurement on the Web: Open Questions From the Privacy Sandbox

Christina Ilvento (Google)

10:30 – 11 a.m.

Break

11 a.m. – 12 p.m.

Privacy Management: Achieving the Possimpible

Laura Brandimarte (University of Arizona)

12 – 2 p.m.

Lunch

2 – 2:45 p.m.

Concurrent Composition Theorems for all Standard Variants of Differential Privacy

Wanrong Zhang (Harvard University)

2:45 – 3:30 p.m.

Chasing the Long Tail: What Neural Networks Memorize and Why

Vitaly Feldman (Apple ML Research)

3:30 – 4 p.m.

Break

4 – 5 p.m.

Panel Discussion

Kimon Drakopoulos, Moon Duchin, Philip LeClerc, Alex Teytelboym, Vahideh Manshadi

5 – 6 p.m.

Reception

9 – 9:30 a.m.

Coffee and Check In

9:30 – 10:15 a.m.

Introduction to (Computational) Redistricting

Moon Duchin (Tufts University)

10:15 – 11 a.m.

A Kerfuffle: Differential Privacy and the 2020 Census

Aloni Cohen (Boston University)

11 – 11:30 a.m.

Break

11:30 a.m. – 12:30 p.m.

Academia, Government, & Industry in the 2020 Disclosure Avoidance System

Philip LeClerc (U.S. Census Bureau)

12:30 – 2 p.m.

Lunch

2 – 2:45 p.m.

Improving Refugee Resettlement

Alex Teytelboym (University of Oxford)

2:45 – 3:30 p.m.

Algorithmic Challenges in Ensuring Fairness at the Time of Decision

Swati Gupta (Georgia Institute of Technology)

3:30 – 4 p.m.

Break

4 – 5 p.m.

Poster Session

9 – 9:30 a.m.

Coffee and Check In

9:30 – 10:15 a.m.

Pipeline Interventions

Juba Ziani (Georgia Tech)

10:15 – 11 a.m.

Bringing Order to Chaos: Navigating the Disagreement Problem in Explainable ML

Hima Lakkaraju (Harvard University)

11 – 11:30 a.m.

Break

11:30 a.m. – 12:30 p.m.

Predictive Modeling in Healthcare – Special Considerations

Noa Dagan (Clalit Health Services)

12:30 – 2 p.m.

Lunch

2 – 2:45 p.m.

What Really Matters for Fairness in Machine Learning: Delayed Impact and Other Desiderata

Lydia Liu (Cornell University)

2:45 – 3:30 p.m.

Supply-Side Equilibria in Recommender Systems

Jacob Steinhardt (UC Berkeley)

3:30 – 4 p.m.

Break

4 – 5 p.m.

Decision-Aware Learning for Global Health Supply Chains

Hamsa Bastani (Wharton School, University of Pennsylvania)

9 – 9:30 a.m.

Coffee and Check In

9:30 – 10:30 a.m.

Unpacking the Black Box: Regulating Algorithmic Decisions

Jann Spiess (Stanford University)

10:30 – 11 a.m.

Break

11 a.m. – 12 p.m.

Efficient and Targeted COVID-19 Border Testing via Reinforcement Learning

Kimon Drakopoulos (University of Southern California)

12 – 2 p.m.

Lunch

2 – 2:45 p.m.

Re-designing Recommendation on VolunteerMatch: Theory and Practice

Vahideh Manshadi (Yale University)

2:45 – 3:45 p.m.

Discussion