Soorati Lab

Human-swarm Interaction: This domain addresses the interaction between humans and multi-agent systems. The goal is to develop effective tools and methods for human operators to interpret and manage multi-agent system actions, ensuring both operational efficiency and adherence to ethical and safety standards.

Swarm Robotics: The research in this area focuses on the design and development of hardware and controllers for robot swarms, enabling them to autonomously execute complex tasks.

Multi-agent Systems: Our research revolves around studying systems with multiple agents. Machine learning techniques are employed to analyze and predict agent behaviors and intentions.

Distributed Machine Learning: A significant part of the research is dedicated to distributed machine learning, which enables the analysis of data spread across multiple devices or nodes. This approach is particularly valuable for designing controllers in real-time systems and for understanding the intricacies of complex natural organisms. By dissecting the inherent mechanisms within these organisms, we can develop more efficient and intelligent multi-agent systems.