Our research initiatives bridge artificial and biological intelligence to solve fundamental challenges in neuroscience and create transformative AI technologies.
Developing advanced algorithms to interpret and translate neural activity into meaningful data, enabling direct brain-computer communication.
Creating artificial neural networks that emulate biological learning processes, leading to more efficient and adaptive AI systems.
Building computational models of human cognition to understand decision-making, memory, and perception at a fundamental level.
Developing minimally invasive interfaces that provide high-bandwidth communication between biological and artificial neural systems.
Nature Neuroscience, 2023
We present a novel transformer-based architecture that achieves state-of-the-art performance in reconstructing visual stimuli from human fMRI data.
Neural Computation, 2023
Our new learning rule demonstrates how spike-timing dependent plasticity can enable efficient unsupervised learning in large-scale neuromorphic systems.
Science Robotics, 2022
Breakthrough in EEG signal processing allows for unprecedented information transfer rates without surgical implantation.
Chief Neuroscience Officer
Formerly at MIT, specializes in cognitive neuroimaging and neural decoding algorithms.
Head of AI Research
Expert in neuromorphic computing and biologically inspired AI architectures.
Lead Neural Engineer
Develops next-generation neural interfaces with expertise in microfabrication.
Collaborate with our team or explore partnership opportunities to advance the frontiers of AI neuroscience.