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About

Mohammad Naiseh is an emerging researcher whose work sits at the intersection of human-computer interaction, explainable AI, and autonomous systems, with a particular focus on human-swarm interaction (HSI). His research investigates how human operators can effectively supervise and collaborate with robot swarms in real-world settings, addressing critical challenges around trust, transparency, and decision-making. Naiseh's most-cited work, "Outlining the Design Space of eXplainable Swarm (xSwarm)" (2024, 11 citations), pioneers a framework for making swarm behaviors interpretable to human operators — a foundational contribution to the nascent field of explainable swarm intelligence. His studies on data visualisation quality and task density reveal how interface design directly shapes human performance in swarm supervision contexts. Notably, his 2024 work on digital twins as a mechanism for building trustworthiness in human-swarm systems offers a practical pathway for deploying these technologies safely. His industry-facing research, including workshop-driven use-case development with operational stakeholders, demonstrates a commitment to translating academic insights into real-world applications. Through a growing publication record spanning user studies, formal modelling, and system design, Naiseh is carving out a distinctive voice in the responsible deployment of autonomous swarm technologies.