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Dr Levin Kuhlmann

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Personal website Epilepsyecosystem.org: Crowdsourcing solutions to seizure prediction

Levin is an Associate Professor in data science, AI and digital health. He is a data scientist, computational neuroscientist and neural engineer. His research areas include signal processing, control theory, machine learning, statistics and computational neuroscience applications to digital health, neural engineering, neuroimaging and medicine.

Supervisor's projects

Project name Sort descending Type
Advanced statistical inference and machine learning for neural modelling, monitoring and imaging Research project
AI-augmented coaching, reporting and its assessment Research project
Brain network mechanisms underlying anaesthetic-induced loss of consciousness Research project
Conscious AI Research project
Continual Few-shot reinforcement learning Honours and Masters project
Creating a 21st Century Helpline for Enhanced Support and Continuity of Care Research project
Creating subject-specific mathematical models to understand the brain Research project
Enhancing Service User Care Pathway Experience through AI-Driven Personalisation Research project
Epileptic Seizure Prediction Research project
Left/Right brain in an RL agent Honours and Masters project
Left/Right brain, human motor control and implications for robotics Honours and Masters project
Left/Right brain, the hippocampus and episodic learning in AI/ML Honours and Masters project
Living AI Research project
Model-based depth of anaesthesia monitoring Research project
RFR: An Actor-Critic Decision-Making Model with the Frontal-Cortex-Basal-Ganglia Loop Honours and Masters project
Self-aware neural networks Research project

Co-supervising

Project name Sort descending Type Primary supervisor
Diagnosis of non-epileptic seizures using multimodal physiological data Honours and Masters project David Dowe
Mind Reading: Translating Brain Activity into Textual Language Honours and Masters project Mahsa Salehi

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Development of a GIS-Based Model for Active Citizenry
Street-Level Environment Recognition On Moving Resource-Constrained Devices
Bayesian Generative AI (PhD Project)
Explainability and Compact representation of K-MDPs
Creating a 21st Century Helpline for Enhanced Support and Continuity of Care

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