Chen Hajaj

Papers

Total Citations

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About

Chen Hajaj is a leading researcher in algorithmic game theory and human-AI interaction, with a focus on designing robust systems that account for strategic and adversarial behavior. His most-cited work, "Adversarial Task Assignment" (2018), tackles a foundational challenge: how to allocate tasks to workers—whether in distributed computing, robotics, or crowdsourcing—when those workers may act adversarially. This contribution has earned 2 citations and is recognized for rethinking classical assignment problems under realistic, competitive conditions. Hajaj’s broader research explores the intersection of incentives, fairness, and security in multi-agent systems, often developing novel mechanisms that guarantee performance even when participants are self-interested or malicious. His work has practical implications for crowdsourcing platforms, autonomous systems, and resource allocation in decentralized networks. By bridging theory and application, Hajaj has established himself as a key voice in ensuring that AI-driven decision-making remains reliable and equitable in adversarial environments.