Research

Research Areas

Trustworthy, resilient, and generalizable AI for networked and cyber-physical systems, with emphasis on 6G and beyond.

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Semantic Communications

Meaning-aware communication that transmits concepts, intent, and task-relevant information.

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Foundation Models for Networks

Large-scale models for network reasoning, control, diagnosis, and adaptation.

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Mathematical Foundations of AI

Causal reasoning, Bayesian inference, game theory, optimization, and interpretable AI.

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Integrated Sensing and Communication

Joint sensing, communication, and computation for AI-native wireless and cyber-physical systems.

Research vision

TRAIN Lab explores foundational questions at the intersection of machine learning, wireless communication, and control theory. The goal is to enable AI systems that are high-performing, interpretable, robust to uncertainty, and aligned with physical and operational constraints.