Joonghui Cho
Korea Advanced Institute of Science and Technology (KAIST)
Builder The claim is about what the hardware does, and the philosophy is left open
Joonghui Cho is a computational neuroscience and machine learning researcher at the Korea Advanced Institute of Science and Technology (KAIST). Working with Minchan Kang and Daeshik Kim, Cho studies how complete biological wiring diagrams obtained from electron microscopy perform when repurposed as recurrent neural network topologies.
In the October 2026 paper A Drosophila Whole-Connectome Network Can Learn Human-Designed Cognitive Tasks (arXiv:2610.10014), Cho, Kang, and Kim instantiate the adult male fruit fly central nervous system connectome (MaleCNS v1.0, comprising 166,700 neurons and 25.5 million directed anatomical edges) as a fixed recurrent graph. By training only a single scalar weight per anatomical edge while keeping input and readout projections fixed, they show that the biological connectome reaches 92.77 percent accuracy on bounded addition and 61.59 percent on grounded relational language tasks, outperforming degree-preserving random rewires by wide margins.
Cho carries the Builder classification because his work tests the computational inductive bias of biological connectomes rather than proposing a philosophical theory of phenomenal consciousness. His results nonetheless sharpen whole-brain emulation debates by showing that evolved microcircuit motifs carry general-purpose recurrent routing capacity beyond native insect reflexes.
Known for. Drosophila MaleCNS whole-connectome cognitive task learning, anatomical inductive bias in recurrent neural networks
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Joonghui Cho 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.