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workflow optimization • Network, graph, and agent-based modeling for care delivery • Health equity, patient access, and system resilience • Multi-modal data integration using EHR, claims, environmental, and
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architecture and design for complex socio-technical systems Graph theory, network science, and knowledge representation Agent-based and simulation modeling AI/ML, foundation models, causal inference, and
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: • Transportation systems modeling and simulation, including O/D modeling, multimodal network modeling, agent-based or behavioral modeling • Large-scale computing, cloud-native analytics workflows, and data
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simulation, including O/D modeling, multimodal network modeling, agent-based or behavioral modeling Large-scale computing, cloud-native analytics workflows, and data engineering for mobility platforms AI/ML
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research encompasses (but is not limited to) identifying effective tutoring practices, running experiments on AI tutors in simulated and real-world environments, fine-tuning AI models to classify qualitative
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not limited to) identifying effective tutoring practices, running experiments on AI tutors in simulated and real-world environments, fine-tuning AI models to classify qualitative data, and building