Incentive design and market evolution of mobile user-provided networks. - Mohammad Mahdi Khalili; Lin Gao 001; Jianwei Huang 001; Babak Hossein Khalaj (INFOCOM Workshops, 2015)

Embracing risk dependency in designing cyber-insurance contracts. - Mohammad Mahdi Khalili; Parinaz Naghizadeh; Mingyan Liu (Allerton, 2017)

Designing Cyber Insurance Policies: Mitigating Moral Hazard Through Security Pre-Screening. - Mohammad Mahdi Khalili; Parinaz Naghizadeh; Mingyan Liu (GAMENETS, 2017)

Designing cyber insurance policies in the presence of security interdependence. - Mohammad Mahdi Khalili; Parinaz Naghizadeh; Mingyan Liu (NetEcon@EC, 2017)

Recycled ADMM: Improve Privacy and Accuracy with Less Computation in Distributed Algorithms. - Xueru Zhang; Mohammad Mahdi Khalili; Mingyan Liu (Allerton, 2018)

Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms. - Xueru Zhang; Mohammad Mahdi Khalili; Mingyan Liu (ICML, 2018)

Designing Cyber Insurance Policies: The Role of Pre-Screening and Security Interdependence. - Mohammad Mahdi Khalili; Parinaz Naghizadeh; Mingyan Liu (IEEE Trans. Inf. Forensics Secur., 2018)

Effective Premium Discrimination for Designing Cyber Insurance Policies with Rare Losses. - Mohammad Mahdi Khalili; Xueru Zhang; Mingyan Liu (GameSec, 2019)

Contract design for purchasing private data using a biased differentially private algorithm. - Mohammad Mahdi Khalili; Xueru Zhang; Mingyan Liu (NetEcon@SIGMETRICS, 2019)

Incentivizing effort in interdependent security games using resource pooling. - Mohammad Mahdi Khalili; Xueru Zhang; Mingyan Liu (NetEcon@SIGMETRICS, 2019)

Long term impact of fair machine learning in sequential decision making: representation disparity and group retention. - Xueru Zhang; Mohammad Mahdi Khalili; Cem Tekin; Mingyan Liu (CoRR, 2019)

Embracing and controlling risk dependency in cyber-insurance policy underwriting. - Mohammad Mahdi Khalili; Mingyan Liu; Sasha Romanosky (J. Cybersecur., 2019)

A Continuously Updated, Computationally Efficient Stress Recognition Framework Using Electroencephalogram (EEG) by Applying Online Multitask Learning Algorithms (OMTL). - Houtan Jebelli; Mohammad Mahdi Khalili; SangHyun Lee (IEEE J. Biomed. Health Informatics, 2019)

Games on Networks with Community Structure: Existence, Uniqueness and Stability of Equilibria. - Kun Jin; Mohammad Mahdi Khalili; Mingyan Liu (ACC, 2020)

A genetic algorithm for selecting cooperative or direct communications between nodes in wireless sensor networks. - Mahdi Khalili; Mohammad Khalily Dermany (Iran J. Comput. Sci., 2020)

Recycled ADMM: Improving the Privacy and Accuracy of Distributed Algorithms. - Xueru Zhang; Mohammad Mahdi Khalili; Mingyan Liu (IEEE Trans. Inf. Forensics Secur., 2020)

Improving Fairness and Privacy in Selection Problems. - Mohammad Mahdi Khalili; Xueru Zhang; Mahed Abroshan; Somayeh Sojoudi (AAAI, 2021)

A Mechanism Design Approach to Solve Ransomware Dilemmas. - Iman Vakilinia; Mohammad Mahdi Khalili; Ming Li 006 (GameSec, 2021)

Trading Privacy through Randomized Response. - Mohammad Mahdi Khalili; Iman Vakilinia (INFOCOM Workshops, 2021)

Fair Sequential Selection Using Supervised Learning Models. - Mohammad Mahdi Khalili; Xueru Zhang; Mahed Abroshan (NeurIPS, 2021)

Designing Contracts for Trading Private and Heterogeneous Data Using a Biased Differentially Private Algorithm. - Mohammad Mahdi Khalili; Xueru Zhang; Mingyan Liu (IEEE Access, 2021)

Resource Pooling for Shared Fate: Incentivizing Effort in Interdependent Security Games Through Cross-Investments. - Mohammad Mahdi Khalili; Xueru Zhang; Mingyan Liu (IEEE Trans. Control. Netw. Syst., 2021)

An Information-theoretical Approach to Semi-supervised Learning under Covariate-shift. - Gholamali Aminian; Mahed Abroshan; Mohammad Mahdi Khalili; Laura Toni; Miguel R. D. Rodrigues (AISTATS, 2022)

Towards Fair Representation Learning in Knowledge Graph with Stable Adversarial Debiasing. - Yihe Wang; Mohammad Mahdi Khalili; Xiang Zhang 012 (ICDM (Workshops), 2022)

Fairness Interventions as (Dis)Incentives for Strategic Manipulation. - Xueru Zhang; Mohammad Mahdi Khalili; Kun Jin; Parinaz Naghizadeh; Mingyan Liu (ICML, 2022)

Incentive Mechanisms for Strategic Classification and Regression Problems. - Kun Jin; Xueru Zhang; Mohammad Mahdi Khalili; Parinaz Naghizadeh; Mingyan Liu (EC, 2022)

RewardRating: A Mechanism Design Approach to Improve Rating Systems. - Iman Vakilinia; Peyman Faizian; Mohammad Mahdi Khalili (Games, 2022)

Symbolic Metamodels for Interpreting Black-Boxes Using Primitive Functions. - Mahed Abroshan; Saumitra Mishra; Mohammad Mahdi Khalili (AAAI, 2023)

Loss Balancing for Fair Supervised Learning. - Mohammad Mahdi Khalili; Xueru Zhang; Mahed Abroshan (ICML, 2023)

Counterfactually Fair Representation. - Zhiqun Zuo; Mahdi Khalili; Xueru Zhang (NeurIPS, 2023)

Federated Learning with Reduced Information Leakage and Computation. - Tongxin Yin; Xueru Zhang; Mohammad Mahdi Khalili; Mingyan Liu (CoRR, 2023)

Differentially Private Real-Time Release of Sequential Data. - Xueru Zhang; Mohammad Mahdi Khalili; Mingyan Liu (ACM Trans. Priv. Secur., 2023)

Imposing Fairness Constraints in Synthetic Data Generation. - Mahed Abroshan; Andrew Elliott; Mohammad Mahdi Khalili (AISTATS, 2024)

Privacy-Aware Randomized Quantization via Linear Programming. - Zhongteng Cai; Xueru Zhang; Mohammad Mahdi Khalili (UAI, 2024)

ECG Signal Denoising Using Multi-scale Patch Embedding and Transformers. - Ding Zhu; Vishnu Kabir Chhabra; Mohammad Mahdi Khalili (CoRR, 2024)

Learning under Imitative Strategic Behavior with Unforeseeable Outcomes. - Tian Xie; Zhiqun Zuo; Mohammad Mahdi Khalili; Xueru Zhang (Trans. Mach. Learn. Res., 2024)

Federated Learning with Reduced Information Leakage and Computation. - Tongxin Yin; Xuwei Tan; Xueru Zhang; Mohammad Mahdi Khalili; Mingyan Liu (Trans. Mach. Learn. Res., 2024)

Lookahead Counterfactual Fairness. - Zhiqun Zuo; Tian Xie; Xuwei Tan; Xueru Zhang; Mohammad Mahdi Khalili (Trans. Mach. Learn. Res., 2024)

Against the opacity, and for a qualitative understanding, of artificially intelligent technologies. - Mahdi Khalili (AI Ethics, 2024)

Mitigating Bias in Machine Learning: A Comprehensive Review and Novel Approaches. - Mahdi Khalili (AAAI, 2025)

Post-processing for Fair Regression via Explainable SVD. - Zhiqun Zuo; Ding Zhu; Mohammad Mahdi Khalili (AISTATS, 2025)

Neuroplasticity and Corruption in Model Mechanisms: A Case Study Of Indirect Object Identification. - Vishnu Kabir Chhabra; Ding Zhu; Mohammad Mahdi Khalili (NAACL (Findings), 2025)

An Efficient Training Algorithm for Models with Block-wise Sparsity. - Ding Zhu; Zhiqun Zuo; Mohammad Mahdi Khalili (Trans. Mach. Learn. Res., 2025)

Towards Understanding and Improving Refusal in Compressed Models via Mechanistic Interpretability. - Vishnu Kabir Chhabra; Mohammad Mahdi Khalili (CoRR, 2025)

From Emergence to Control: Probing and Modulating Self-Reflection in Language Models. - Xudong Zhu; Jiachen Jiang; Mohammad Mahdi Khalili; Zhihui Zhu (CoRR, 2025)

On the transferability of Sparse Autoencoders for interpreting compressed models. - Suchit Gupte; Vishnu Kabir Chhabra; Mohammad Mahdi Khalili (CoRR, 2025)