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developing or applying parallel algorithms and scalable workflows for HPC resources. Experience developing or applying privacy-enhancing technologies such as federated learning, differential privacy, and
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, Mixture-of-Experts; distributed training/inference (e.g. FSDP, DeepSpeed, Megatron-LM, tensor/sequence parallelism); scalable evaluation pipelines for reasoning and agents. Federated & Collaborative
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leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration
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