442 Smith Hall
Newark, Delaware 19716
PostDoc | 2020 | UC Berkeley
Ph.D. | 2019 | University of Michigan, Ann Arbor | Electrical Engineering and Computer Science (EECS)
MSc | 2018 | University of Michigan, Ann Arbor | Applied Math
MSc in Electrical Engineering, 2015, Sharif University of Technology
BSc | 2013 | Sharif University of Technology | Electrical Engineering
My research interest is in the societal aspect of machine learning, specifically in the areas of data privacy, fairness, game theory and mechanism design, and security economics.
1. MM. Khalili, X. Zhang. M. Liu, “Resource Pooling for Shared Fate: Incentivizing Effort in Interdependent Security Games through Cross-investments”, to appear in IEEE Transactions on Control and Network Systems, 2020.
2. X. Zhang*, MM. Khalili*, C. Tekin, M. Liu, “Group Retention when Using Machine Learning in Sequential Decision Making: the Interplay between User Dynamics and Fairness”, NuerIPS 2019. (*Equal Contribution)
3. MM. Khalili, M. Liu, S. Romanosky, “Embracing and Controlling Risk Dependency in Cyber Insurance Policy Underwriting”, Journal of Cyber Security, 2019.
4. MM. Khalili, X. Zhang, M. Liu, “Contract design for purchasing private data using a biased differentially private algorithm”, Workshop on the Economics of Networks, Systems and Computation, 2019.
5. X. Zhang, MM. Khalili, M. Liu, “Recycled ADMM: Improving the Privacy and Accuracy of Distributed Algorithms”. IEEE Transactions on Information Forensics and Security, 2019.
6. MM. Khalili, P. Naghizadeh, M. Liu, “Designing Cyber Insurance Policies: The Role of Pre-Screening and Security Interdependence”, IEEE Transactions on Information Forensics and Security, 2018.
7. X. Zhang, MM. Khalili, M. Liu, “Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms”, International Conference on Machine Learning, 2018.
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