Assured Information Management and Sharing (AIMS)

Department of Computer Science
Emory University

Enabling trustworthy and privacy-preserving data sharing is key to addressing critical issues as diverse as healthcare and national security. The AIMS research lab conducts research in the intersection of big data, machine learning, and information privacy and security aimed at developing algorithms and techniques for enhancing privacy and robustness for the life cycle of data driven systems including data aquisition, data sharing, and machine learning.

Current Projects
Decentralized differentially-private methods for dynamic data release and analysis (NIH R01 renewal) (PI: Lucila Ohno-Machado at UCSD, Xiaoqian Jiang at UTHealth), 2022-2025

Hyperlocal Risk Monitoring and Pandemic Preparedness through Privacy-Enhanced Mobility and Social Interactions Analysis (NSF SCC) (with Weihua An, Shivani Patel at Emory, Cyrus Shahabi at USC, Masatoshi Yoshikawa and collaborators at Kyoto University and NAIST), 2021-2024

PREMED: Privacy-Preserving and Robust Computational Phenotyping using Multisite EHR Data (NSF SaTC) (with Joyce Ho, Gari Clifford and Siva Bhavani at Emory, Xiaoqian Jiang and Paul Schulz at UTHealth), 2021-2025

Healthcare Recommender Systems (Kaiser Permanente Digital), 2022 – 2023

Wearable Home Monitors for ALS (Mitsubishi Pharma America), 2021 - 2022  

Machine Learning for Multi-Modal Sensing Technology for Heat Exposure (Cisco Research University Award) (PI: Vicky Hertzberg), 2021-2022

PREPARE: Virtual Organization for Computing Research in Pandemic Preparedness and Resilience (NSF CNS) (PI: Madhav Marathe at UVA, with Anil Vullikanti at UVA and Simon Levin at Princeton), 2020-2023

Privacy-enhanced data-driven health monitoring for smart and connected senior communities (NSF SCC) (with Gari Clifford and Weihua An at Emory, Masatoshi Yoshikawa and Tomohiro Kuroda at Kyoto University), 2020-2022

TIMES: A tensor factorization platform for spatio-temporal data (NSF BigData) (PI: Joyce Ho at Emory, with Jimeng Sun at UIUC), 2018-2022

Selected Past Projects
Decentralized differentially-private methods for dynamic data release and analysis (NIH R01) (PI: Lucila Ohno-Machado at UCSD, UTHealth: Xiaoqian Jiang), 2017-2022

REACT: Real-time contact tracing and risk monitoring via privacy enhanced mobile tracking (NSF RAPID) (with Vicki Hertzberg and Lance Waller at Emory, Cyrus Shahabi at USC, and Xiaoqian Jiang and Amy Franklin at UTHealth), 2020-2022

Development of a Differentially-Private, Synthetic Control Group for the Center for Health Discovery and Well Being (CHDWB) Cohort (Emory Synergy) (with Lance Waller and Yi-An Ho at Emory), 2020-2021

Spatiotemporal Privacy for Location Based Applications (NSF SaTC), 2016-2020

Next Generation Frameworks for Secure DDDAS/Infosymbiotics Systems (AFOSR DDDAS) (with Vaidy Sunderam at Emory), 2016-2020

Building Patient-Centered Privacy Preserving Data Registries (PCORI) (with Prof. Andrew Post at Emory, Prof. Xiaoqian Jiang at UTHealth, and Prof. Lucila Ohno-Machado at UCSD), 2014-2019

SHARE: Statistical Health Information Release with Differential Privacy (NIH R01) (with Prof. Andrew Post at Emory, Prof. Xiaoqian Jiang at UTHealth, and Prof. Lucila Ohno-Machado at UCSD), 2015-2019

I-Corps: iCloak: Privacy Preserving Individual Location Sharing (NSF I-Corps), 2016-2017

Extending Differential Privacy for Privacy Preserving Location Sharing (Google Research Award), 2016-2017

PREDICT: PRivacy Enhancing Dynamic Information Collection and moniToring (AFOSR DDDAS) (with Prof. Vaidy Sunderam at Emory), 2012-2015

Adaptive Differentially Private Data Release (NSF SaTC), 2011-2015

HIDE™: Health Information DE-identification (Woodrow Wilson Foundation), 2019-2010

Enabling Privacy for Data Federation Services (Cisco Research Award), 2010

FRIL: Fine-grained Record Integration and Linkage (CDC), 2007-2008

Acknowledgement
We acknolwedge the generous support by NSF, AFOSR, NIH, and PCORI, Google Research Award, Woodrow Wilson Foundation, Cisco research award, IBM Faculty Innovation Award, and various support from Emory University (Math/CS, College, PERS, URC, and Synergy).

Any opinions, findings, and conclusions or recommendations expressed in the project material are those of the authors and do not necessarily reflect the views of the sponsors.