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applications such as conversational agents, mental well-being, and education, where emotion safety is crucial; Design interventions to reduce bias and improve fairness and safety in human-AI interaction
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interaction; Design methods and metrics to evaluate bias, fairness, inclusivity, safety, and emotional responsiveness; Explore applications such as conversational agents, mental well-being, and education, where
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of topics include algorithmic fairness in network analysis, developing network embedding frameworks for real-world network datasets or AI models based on agentic LLMs for simulating real-world network data
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