Alexandre Pouget
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Alexandre Pouget
Use the future to build the present
Alexandre Pouget
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1.1Advanced AI1.2QuantumRevolution1.3UnconventionalComputing1.4AugmentedReality1.5CollectiveIntelligence2.1CognitiveEnhancement2.2HumanApplicationsof GeneticEngineering2.3HealthspanExtension2.4ConsciousnessAugmentation2.5Organoids2.6FutureTherapeutics3.1Decarbonisation3.2EarthSystemsModelling3.3FutureFoodSystems3.4SpaceResources3.5OceanStewardship3.6SolarRadiationModification3.7InfectiousDiseases4.1Science-basedDiplomacy4.2Advancesin ScienceDiplomacy4.3Foresight,Prediction,and FuturesLiteracy4.4Democracy-affirmingTechnologies5.1ComplexSystemsScience5.2Futureof Education5.3Future Economics,Trade andGlobalisation5.4The Scienceof theOrigins of Life5.5SyntheticBiology
1.1Advanced AI1.2QuantumRevolution1.3UnconventionalComputing1.4AugmentedReality1.5CollectiveIntelligence2.1CognitiveEnhancement2.2HumanApplicationsof GeneticEngineering2.3HealthspanExtension2.4ConsciousnessAugmentation2.5Organoids2.6FutureTherapeutics3.1Decarbonisation3.2EarthSystemsModelling3.3FutureFoodSystems3.4SpaceResources3.5OceanStewardship3.6SolarRadiationModification3.7InfectiousDiseases4.1Science-basedDiplomacy4.2Advancesin ScienceDiplomacy4.3Foresight,Prediction,and FuturesLiteracy4.4Democracy-affirmingTechnologies5.1ComplexSystemsScience5.2Futureof Education5.3Future Economics,Trade andGlobalisation5.4The Scienceof theOrigins of Life5.5SyntheticBiology

Profile:

Alexandre Pouget

ProfessorUniversity of Geneva
    Alexandre Pouget is currently a full professor in the Neuroscience Center at the University of Geneva, where he leads the computational cognitive neuroscience laboratory. His research focuses on theories of representation and computation in neural circuits with a strong emphasis on neural theories of probabilistic inference. According to this approach, knowledge in the brain takes the form of probability distributions and new knowledge is acquired via probabilistic inferences. This allows robust computations in the presence of uncertainty, a situation that arises in almost all real-life computations. He is currently applying this framework to a wide range of topics including olfactory processing, spatial representations, sensory motor transformations, multisensory integration, perceptual learning, attentional control, decision making, causal reasoning and, more recently, simple arithmetic.