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projects
Circuits for Low-Powered Robotics Applications
Status: In Progress
Interdisciplinary research project combining robotics, physics, and neuroscience to develop energy-efficient circuit designs for low-power applications.
FDTD Simulation from Scratch
Status: Completed | Started:
Parallelized implementation of Finite-Difference Time-Domain (FDTD) simulation using Yee lattice formulation for electromagnetic wave propagation.
MEEP Optics Simulation with Parallel Processing
Status: Completed | Started:
Implementation and testing of the MEEP open-source optics simulation library with enhanced parallel processing capabilities for multi-core CPU systems.
2-D Kuramoto Oscillator Membrane
Status: Completed | Started:
Coupled-oscillator simulation on a 2-D grid illustrating membrane-like neuronal dynamics.
publications
Reduced-Dimension, Biophysical Neuron Models Constructed From Observed Data
Published in Neural Computation, 2022
“Using methods from nonlinear dynamics and interpolation techniques from applied mathematics, we show how to use data alone to construct discrete time dynamical rules that forecast observed neuron properties. These data may come from simulations of a Hodgkin-Huxley (HH) neuron model or from laboratory current clamp experiments. In each case, the reduced-dimension, data-driven forecasting (DDF) models are shown to predict accurately for times after the training period.”
Recommended citation: Randall Clark, Lawson Fuller, Jason A. Platt, Henry D. I. Abarbanel; Reduced-Dimension, Biophysical Neuron Models Constructed From Observed Data. Neural Comput 2022; 34 (7): 1545–1587. doi: https://doi.org/10.1162/neco_a_01515
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talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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