Daniel Gross, PhD, is currently a Senior Gen-AI/Neuro-symbolic Researcher at Swimm, focusing on reliably extracting business knowledge from legacy code. Previously, Daniel held various roles at Modal<>AI, where they developed a novel symbolic AI tool aimed at automating compliance in unpredictable work domains. Earlier in their career, they served as a Principal and Analyst at Goal-Oriented Solutions, contributing to significant advancements in knowledge representation and risk management for software. Daniel has also held positions at General Motors, IBM, and Intel, where they specialized in cognitive computing and knowledge representation. They earned a PhD and have extensive experience in both research and applied technology.
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