Multi-Agent and AI Systems
Multi-agent learning, coordination, task routing, communication-efficient collaboration, and adaptive decision-making among heterogeneous intelligent agents.
ISN Lab develops mathematical and learning-based methods for intelligent systems that must communicate, coordinate, and make decisions under resource and uncertainty constraints.
Information Freshness and Networked Systems
Age of Information, status-update systems, predictive control, and timely decision-making for dynamic communication and cyber-physical systems.
Communication and Resource Optimization
Scheduling, resource allocation, stochastic optimization, and learning-based control for wireless, edge, and distributed computing systems.
Distributed and Federated Learning
Efficient distributed learning under communication, computation, participation, and incentive constraints.
Intelligent Wireless Networks
Learning and optimization for adaptive wireless systems, network control, and AI-native networking.
Satellite and Non-Terrestrial Networks
Timely information delivery and resource-aware optimization in LEO and future integrated networks.