Daeshik Kim
School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST)
Builder The claim is about what the hardware does, and the philosophy is left open
Daeshik Kim is Professor in the School of Electrical Engineering at the Korea Advanced Institute of Science and Technology (KAIST). Trained in cognitive neuroscience and high-field functional magnetic resonance imaging, Kim has spent three decades investigating how physical wiring constraints in visual cortex and whole-organism nervous systems govern information processing.
In October 2026, Kim, Joonghui Cho, and Minchan Kang published A Drosophila Whole-Connectome Network Can Learn Human-Designed Cognitive Tasks (arXiv:2610.10014). Using the 166,700-node MaleCNS v1.0 dataset as a fixed sparse graph and training one scalar weight per directed anatomical edge, their team showed that the fruit fly’s native wiring topology outperforms 20 comparative graph families and degree-matched random rewires on arithmetic and relational language benchmarks.
Kim is classified as a Builder on this site. His empirical work isolates what an exact anatomical connectome contributes to recurrent computation before cell-type biophysical dynamics or neuromodulators are added, providing a quantitative baseline for whole-brain emulation roadmaps.
Known for. High-field functional MRI, cortical column mapping, Drosophila whole-connectome recurrent network architectures
Coverage on this site
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Daeshik Kim is listed with the other builders, who hold that the claim is about what the hardware does, and the philosophy is left open. The positions themselves are set out in the index of consciousness theories. Every researcher covered on this site is indexed in the directory of consciousness researchers.