Viktor Rehnberg
Bio
Updated 03/23/26Viktor Rehnberg is a Swedish AI safety researcher based in Gothenburg, Sweden. He holds an M.Sc. in Engineering Physics from Chalmers University of Technology, where he also worked as a Research Engineer at Chalmers e-Commons supporting ML/AI infrastructure. He participated in the SERI MATS (ML Alignment Theory Scholars) Winter 2022 program, conducting research on identifying key steps in reducing risks from learned optimization, including mesa-optimization and inner alignment problems. He has collaborated with Erik Jenner and Oliver Daniels-Koch on empirical mechanistic anomaly detection (MAD) research, co-authoring a LessWrong post on concrete empirical research projects in that area under supervision of John Wentworth and Erik Jenner. He also participated in AI Safety Camp Edition 5, where his team investigated neural network modularity loss functions to improve interpretability. He is an organizer of EA Gothenburg and is motivated by effective altruism, longtermism, and preventing existential risk.
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Links
Updated 03/23/26- Personal Website
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