Li Xiong

Li Xiong
Samuel Candler Dobbs Professor of Computer Science 
Assured Information Mangement and Sharing (AIMS) Lab
Department of Computer Science
Department of Biomedical Informatics
Emory University

Address: 400 Dowman Dr, Atlanta, GA 30322
Office: Mathematics and Science Center E412
Phone: 404-727-0758, Fax: 404-727-5611
Email: lxiong AT

Google Scholar Profile | DBLP Entry


News and Activities

Looking for postdoc and PhD students!

November 2023: Gave an invited talk on "Supporting pandemic preparedness with Privacy Enhancing Technology" at IEEE TPS 2023

July 2023: Gave an invited talk on "Federated Learning with Personalized and User-level Differential Privacy" in FL@ICML 2023. Upcoming keynote on "Harnessing Spatiotemporal Data for Pandemic Preparedness with Privacy-Enhancing Technologies (PETs)" for SSTD 2023!

May 2023: Starting a new project funded by the IARPA HAYSTAC program, led by Novateur and in collaboration with USC, UMN, UCSD, CMU, UCLA, and UC Berkeley.

April 2023: Congratulations to Fereshteh Razmi for defending her PhD thesis and Matt Zhang, Kevin Qin, Mike Lin, Jack Wessell for defending their honor thesis's with highest honor!

February 2023: Starting a new project on Understanding Bias in AI Models for the Prediction of Infectious Disease Spread funded by NSF and CSIRO, led by Prof. Andreas Zufle at Emory and Prof. Flora Salim at UNSW Sydney.

[Archive of News and Activiities]

Brief Bio
Li Xiong is a Samuel Candler Dobbs Professor of Computer Science and Professor of Biomedical Informatics at Emory University. She held a Winship Distinguished Research Professorship from 2015-2018. She has a Ph.D. from Georgia Institute of Technology, an MS from Johns Hopkins University, and a BS from the University of Science and Technology of China. Her research lab, Assured Information Management and Sharing (AIMS), conducts research in the intersection of data management, machine learning, and data privacy and security, with a recent focus on privacy-enhancing and trustworthy machine learning and data sharing algorithms to advance data driven-AI systems for healthcare, public health, and spatial intelligence. She has published over 180 papers and received six best paper or runner up awards. She has served and serves as associate editor for IEEE TKDE, IEEE TDSC, and VLDBJ, general chair for ACM SIGSPATIAL 2024, CIKM 2022, program chair for IEEE BigData 2020 and ACM SIGSPATIAL 2020, 2018, tutorial chair for VLDB 2024, program vice-chair for VLDB 2024, ACM SIGMOD 2024, 2022, and IEEE ICDE 2023, 2020. Her research is supported by federal agencies including NSF, NIH, IARPA, AFOSR, PCORI, and industry awards including Google, IBM, Mitsubishi, Cisco, AT&T, and Woodrow Wilson Foundation. She is an IEEE fellow.