David Krueger is an Assistant Professor in the Machine Learning Group at the University of Cambridge's Department of Engineering. His primary research interests lie in the field of artificial intelligence, with a specific focus on deep learning theory, AI safety, alignment, and interpretability. He aims to develop AI systems that are more robust, reliable, understandable, and beneficial to society. His work often explores how to ensure that powerful AI systems behave as intended and avoid unintended negative consequences.
David Krueger's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
He heads a research group at the University of Cambridge focused on foundational and applied problems in AI safety, alignment, and deep learning, contributing to the development of more trustworthy AI systems.
Author and co-author of numerous impactful publications in top-tier machine learning conferences (e.g., NeurIPS, ICML, ICLR) and journals, advancing the understanding of deep learning phenomena, robustness, and out-of-distribution generalization.
Actively contributes to the discourse on AI safety and the long-term implications of artificial intelligence, often speaking at workshops and engaging with the broader research community on these critical topics.
Has been involved in organizing research programs and workshops, such as AI Safety Camp (now part of an AGI Safety Fundamentals Program), fostering collaboration and new talent in the field.
University of Wisconsin-Madison
Cardinal Stritch University
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