Neuromorphic Machine Intelligence Lab
Cognition, Neuroscience and Machine Learning
Dr. Emre Neftci received his degree in Physics at EPF Lausanne and his PhD with Prof. Indiveri in Neuroinformatics at the Institute of Neuroinformatics, ETH Zurich. His thesis described a methodology for synthesizing state-dependent computations in mixed-signal neuromorphic systems. Later, in 2012, Dr. Neftci joined the Insitute of Neural Computation (INC), UC San Diego as a post-doctoral fellow in the lab of Gert Cauwenberghs to investigate models for probabilistic state-dependent sensorimotor processing in large-scale multi-neuron systems. Since 2015, Dr. Neftci is an assistant professor in the department of Cognitive Sciences at UC Irvine. His current research focuses on theoretical and computational modeling of learning in neural systems that exploit the characteristics of neuromorphic hardware.
Georgios Detorakis holds a degree in Applied Mathematics from the University of Crete, a master degree in Brain and Mind Sciences from the University of Crete and he received his PhD in Computational Neuroscience at INRIA and University of Lorraine, France. His thesis focused on modeling the topographic organization of a part of primary somatosensory cortex of monkeys using the theory of neural fields as computational/mathematical framework.
As a post-doc researcher at CentraleSupelec (France) and as member of the ANR project "SynchNeuro", he studied the closed-loop deep brain stimulation technique for the treatment of Parkinson's diseade symptoms. He mainly used computational/mathematical models and he conducted analytical work as well collaborating with control theory scientists. Furthermore, he involved in the development of spike sorting software as part of the same project. Finally, he has experience in recording techniques such as EEG and EMG.
Jordan Ali Rashid is a doctoral student in cognitive science, native Floridian, and son of Ismaili immigrants. He was educated by the Jesuits since grade school, and in 2013 received his bachelor degree from Loyola, Chicago in Psychology and Neuroscience. As an undergraduate, Jordan developed a passion for psychophysics working with Dr. Anne Sutter and Dr. Raymond Dye. His undergraduate research interests focused on word recognition, specifically the priming effects of structural regularities in word forms and the grammatical constraints those forms impose. Jordan received his Masters in cognitive neuroscience from the University of California, Irvine in 2016. His thesis in psychophysics addressed the cognitive strategies and neural mechanisms available to humans for extracting summary and statistical representations of visual objects. Since then, Jordan has become interested in applying dynamic models of visual attention to neuromorphic sensing and processing. Currently his work focuses on developing an architecture that performs Bayesian inference on event-based sensory signals that are encoded to maximize efficiency, subject to neuromorphic hardware constraints.
Dan Barsever received the B.S. degree in Electrical Engineering from University of California, Irvine in 2016. He is currently a graduate student working in the Neuromorphic Machine Intelligence Lab towards a Ph.D. in Cognitive Sciences with a concentration in Cognitive Neuroscience. His research interests include brain-computer interfacing, human augmentation, artificial intelligence, and neural modeling.