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limited to) performance tracing for improved scalability, energy efficiency and fault tolerance in ML training / inference. We seek to improve our AI and machine learning work by bringing in tools to assist
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collaborators. Your work will develop algorithms, inference methods, and frameworks to adapt models from training data to test environments, which is necessary to resolve distribution shifts, hidden confounders
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to polarization. Leveraging network science, NLP, behavioral sensing, and causal inference, the project pioneers new methods for detecting and mitigating online harms. Its results aim to inform public health
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