Privacy and Ethics in Pandemic Data Collection and Processing
Institute for Computational and Experimental Research in Mathematics (ICERM)
January 17, 2023 - January 20, 2023
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Tuesday, January 17, 2023
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8:45 - 9:00 am ESTCheck In11th Floor Collaborative Space
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9:00 - 9:15 am ESTWelcome11th Floor Lecture Hall
- Session Chair
- Brendan Hassett, ICERM/Brown University
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9:15 - 10:00 am ESTOpening plenary: Introduction to MAPPS; Participant introductionsOpening Remarks - 11th Floor Lecture Hall
- Mark Lurie, Brown University
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10:00 - 10:30 am ESTCoffee Break11th Floor Collaborative Space
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10:30 - 11:15 am ESTKeynote: Modeling epidemics with network data11th Floor Lecture Hall
- Speaker
- Samuel Scarpino, Northeastern University
- Session Chair
- Jeremy Goldhaber-Fiebert, Stanford University
Abstract
The COVID-19 pandemic has upended our societies and re-shaped the way we go about our day-to-day lives—from how we work and interact to the way we buy groceries and attend school. In this talk, I will present a series of studies exploring how our behavior, mobility patterns, and social networks have altered and been altered by COVID-19. Leveraging global data sets that represent billions of people, I will show how myriad factors interacted to shape the course of the pandemic. Using the lessons learned from COVID-19, I will discuss how we might balance the ethical and privacy considerations around high-resolution mobility data with their critical role in responding to epidemics.
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11:15 am - 12:00 pm ESTKeynote: Privacy and epidemic modeling11th Floor Lecture Hall
- Speaker
- Katrina Ligett, Hebrew University of Jerusalem
- Session Chair
- Jeremy Goldhaber-Fiebert, Stanford University
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12:00 - 1:30 pm ESTLunch/Free Time
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1:30 - 2:30 pm ESTSession: Envisioning the data needs of MAPPING@Brown11th Floor Lecture Hall
- Speakers
- Jason Gantenberg, Brown University
- Kimani Toussaint, Brown University
- Thomas Trikalinos, Brown University
- Guixing Wei, Brown University
- Session Chair
- Mark Lurie, Brown University
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2:30 - 3:00 pm ESTCoffee Break11th Floor Collaborative Space
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3:00 - 4:30 pm ESTBreakout 1: Data needs for MAPPING@Brown - led by Mark LurieGroup Work
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4:30 - 5:00 pm ESTReport-outs and InstructionsGroup Presentations - 11th Floor Lecture Hall
- Session Chair
- Mark Lurie, Brown University
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5:00 - 6:30 pm ESTReception11th Floor Collaborative Space
Wednesday, January 18, 2023
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8:45 - 9:00 am ESTCheck In11th Floor Collaborative Space
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9:00 - 9:15 am ESTWelcome11th Floor Lecture Hall
- Session Chair
- Megan Ranney, Brown University
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9:15 - 10:00 am ESTKeynote: Synthetic data for network modeling11th Floor Lecture Hall
- Speaker
- Adam Smith, Boston University
- Session Chair
- Anna Lysyanskaya, Brown University
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10:00 - 10:30 am ESTCoffee Break11th Floor Collaborative Space
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10:30 - 11:15 am ESTKeynote: Key concerns and principles for large-scale data collections and surveillance11th Floor Lecture Hall
- Speaker
- Julia Netter, Brown University
- Session Chair
- Wilmot James, Columbia University
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11:15 am - 12:00 pm ESTKeynote: Differential privacy in graphs11th Floor Lecture Hall
- Speaker
- Sofya Raskhodnikova, Boston University
- Session Chair
- Wilmot James, Columbia University
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12:00 - 1:00 pm ESTLunch/Free Time
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1:00 - 1:30 pm ESTPrep for BreakoutsGroup Work - 11th Floor Lecture Hall
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1:30 - 2:30 pm ESTBreakout 2: Privacy and data collection in the context of MAPPING@Brown - led by Julia NetterGroup Work
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2:30 - 3:00 pm ESTCoffee Break11th Floor Collaborative Space
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3:00 - 4:30 pm ESTBreakout 3: Applications of differential privacy for MAPPING@Brown - led by Anna LysyanskayaGroup Work - 11th Floor Lecture Hall
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4:30 - 5:00 pm ESTReport-outs and InstructionsGroup Presentations - 11th Floor Lecture Hall
- Session Chair
- Julia Netter, Brown University
Thursday, January 19, 2023
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8:45 - 9:00 am ESTCheck In11th Floor Collaborative Space
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9:00 - 9:15 am ESTIntroductory Remarks and Breakout PrepOpening Remarks - 11th Floor Lecture Hall
- Session Chair
- Thomas Trikalinos, Brown University
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9:15 - 10:00 am ESTKeynote: A Forecasting epidemiological patterns using multi-scale semi-mechanistic models11th Floor Lecture Hall
- Speaker
- Gerardo Chowell, Georgia State University
- Session Chair
- George Mohler, Boston College
Abstract
The COVID-19 pandemic has highlighted the urgent need to develop reliable tools to forecast the trajectory of epidemics and pandemics in near real time. We describe and apply an ensemble n-sub-epidemic modeling framework for predicting the course of epidemics and pandemics. We systematically assess its calibration and short-term forecasting performance and compare it with other competitive statistical models. This sub-epidemic framework has demonstrated reliable forecasting performance in the context of COVID-19 and monkeypox epidemics.
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10:00 - 10:30 am ESTCoffee Break11th Floor Collaborative Space
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10:30 am - 12:00 pm ESTBreakout 4: Design and Anaylsis of a MAPPING@Brown embedded simulation - led by Thomas Trikalinos and Jason GantenbergGroup Work
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12:00 - 1:00 pm ESTLunch/Free Time
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1:00 - 1:15 pm ESTPrep for BreakoutGroup Work - 11th Floor Lecture Hall
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1:15 - 2:00 pm ESTState of the sciene: Multiparty computation11th Floor Lecture Hall
- Speaker
- Peihan Miao, Brown University
- Session Chair
- Anna Lysyanskaya, Brown University
Abstract
Secure Multi-Party Computation (MPC) enables multiple entities to perform joint computations on their private data without exposing the data to one another. Since its introduction in the 1980s, MPC has been one of the most active research areas in cryptography, due in part to its wide applications and promising security guarantees. Over the last decade, MPC has gradually progressed from being purely of theoretical interest to being adopted more and more in practice. Yet, the adoption of MPC in real-world settings is still very limited as of today. In light of the recent data privacy legislations, there is an urgent need for bridging the gap between the theoretical feasibility and practical efficiency of MPC. Research in this area spans both theoretical and applied cryptography. In theory, we develop new techniques for achieving general MPC with the optimal complexity, bringing theory closer to practice. In practice, we design tailored MPC to achieve the best concrete efficiency for specific real-world applications. In this talk, I will discuss the challenges in both directions and how to overcome these challenges using cryptographic approaches.
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2:00 - 2:45 pm ESTKeynote: Efficient and scalable muliparty computation11th Floor Lecture Hall
- Speaker
- Vlad Kolesnikov, Georgia Institute of Technology
- Session Chair
- Anna Lysyanskaya, Brown University
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2:45 - 3:15 pm ESTCoffee Break11th Floor Collaborative Space
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3:15 - 4:45 pm ESTBreakout 5: Multi-party computation for analyzing MAPPING@Brown mobility data - led by Anna LysyankayaGroup Work
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4:45 - 5:00 pm ESTReport-outs and InstructionsGroup Presentations - 11th Floor Lecture Hall
- Session Chair
- Anna Lysyanskaya, Brown University
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6:30 - 7:30 pm ESTDinner at Waterman GrilleExternal Event
Friday, January 20, 2023
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9:00 - 9:30 am ESTCheck In11th Floor Collaborative Space
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9:30 - 10:45 am ESTHighlights and Discussion - Flipped PannelClosing Remarks - 11th Floor Lecture Hall
- Session Chair
- Jason Gantenberg, Brown University
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10:45 - 11:00 am ESTCoffee Break11th Floor Collaborative Space
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11:00 am - 12:00 pm ESTSynthesis Session: Envisioning the next 5 yearsProblem Session - 11th Floor Lecture Hall
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12:00 - 1:30 pm ESTLunch & DepartureLunch/Free Time
All event times are listed in ICERM local time in Providence, RI (Eastern Daylight Time / UTC-4).
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