Zhiyu Wan is a postdoctoral research fellow in the Department of Biomedical Informatics at Vanderbilt University Medical Center. He is mentored by Dr. Bradley A. Malin, and is currently working in the Health Information Privacy Laboratory (HIPLAB) and the Center for Genetic Privacy and Identity in Community Settings (GetPreCiSe) at Vanderbilt University.
He holds a PhD in Computer Science from Vanderbilt University. He obtained his bachelor’s degree in Automation from Xi’an Jiaotong University.
His research interests include: optimizing privacy-preserving data sharing, with an emphasis on health and genomic data; leveraging game theory, artificial intelligence, and machine learning techniques to improve social good; and analyzing social networks and network security.
Experience
2021–present
Postdoctoral Research Fellow, Vanderbilt University Medical Center
2013–2020
Research Assistant, Vanderbilt University
2012–2013
Teaching Assistant, Vanderbilt University
Publications
2021
Enabling Realistic Health Data Re-identification Risk Assessment Through Adversarial Modeling, Journal of the American Medical Informatics Association
2020
Game Theory for Privacy-Preserving Sharing of Genomic Data, Responsible Genomic Data Sharing: Challenges and Approaches
2019
Biomedical Research Cohort Membership Disclosure on Social Media, Proceedings of the 2019 American Medical Informatics Association Annual Fall Symposium
2018
Detecting the Presence of an Individual in Phenotypic Summary Data, Proceedings of the 2018 American Medical Informatics Association Annual Fall Symposium
2018
It’s all in the timing: Calibrating temporal penalties for biomedical data sharing, Journal of the American Medical Informatics Association
2017
Controlling the Signal: Practical Privacy Protection of Genomic Data Sharing In Beacon Services, BMC Medical Genomics
2017
Expanding Access to Large-Scale Genomic Data While Promoting Privacy: A Game Theoretic Approach, The American Journal of Human Genetics
2017
An Open Source Tool for Game Theoretic Health Data De-identification, Proceedings of the 2017 American Medical Informatics Association Annual Fall Symposium
2015
A Game Theoretic Framework for Analyzing Re-Identification Risk, PLoS ONE
2015
Process-Driven Data Privacy, Proceedings of the 24th ACM International on Conference on Information and Knowledge Management
2010
Honeynet-based collaborative defense using improved highly predictive blacklisting algorithm, Proceedings of 8th World Congress on Intelligent Control and Automation