Imperial College London

Dr Dan Goodman

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Senior Lecturer



+44 (0)20 7594 6264d.goodman Website




1001Electrical EngineeringSouth Kensington Campus





The aim of my research is to uncover the principles underlying neural computation with precisely timed spikes. This is a form of computation specific to the brain, being radically different to both digital and analogue computation. I have developed several software tools for working with spiking neurons, notably the "Brian" spiking neural network simulator. My focus is on sensory processing of complex, realistic stimuli, primarily in the auditory system.

For more information, see my group webpage, the Neural Reckoning Group.



Engel Alonso Martinez J, Goodman D, Picinali L, 2022, Assessing HRTF preprocessing methods for Ambisonics rendering through perceptual models, Acta Acustica -peking-, Vol:6, ISSN:0371-0025

Perez-Nieves N, Leung VCH, Dragotti PL, et al., 2021, Neural heterogeneity promotes robust learning, Nature Communications, Vol:12, Pages:5791-5791

Su Y, Chung Y, Goodman DFM, et al., 2021, Rate and Temporal Coding of Regular and Irregular Pulse Trains in Auditory Midbrain of Normal-Hearing and Cochlear-Implanted Rabbits, Jaro-journal of the Association for Research in Otolaryngology, Vol:22, ISSN:1525-3961, Pages:319-347

Weerts L, Rosen S, Clopath C, et al., 2021, The Psychometrics of Automatic Speech Recognition


Engel Alonso Martinez J, Goodman DFM, Picinali L, Improving Binaural Rendering with Bilateral Ambisonics and MagLS, DAGA 2021

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