Papers
5
Total Citations
72
H-Index
3
About
Yazan Mualla is a researcher at the forefront of explainable artificial intelligence (XAI) and human-agent interaction, with a particular focus on making intelligent, autonomous systems—such as drones and robots—transparent and trustworthy for human users. His most influential work, "The quest of parsimonious XAI: A human-agent architecture for explanation formulation" (2021, 54 citations), introduces a novel framework that balances the depth of explanations with cognitive simplicity, a critical challenge in deploying AI in real-world settings. Mualla further refines this domain by clarifying the intersection of human-computer interaction and explainability in a 2023 paper (8 citations), providing essential terminology for the field. Beyond foundational theory, he applies these principles to practical challenges, including decentralized multi-agent fleet management for remote drones (2022, 5 citations) and traffic signal management in developing countries (2022, 2 citations), where his work addresses social behaviors and infrastructure constraints. By bridging the gap between complex AI decision-making and human understanding, Mualla’s research is paving the way for safer, more collaborative human-robot systems, with growing impact across robotics, autonomous systems, and human-computer interaction communities.
Research Focus
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