Wingert, J. C., Parida, S., Norman-Haignere, S., & David, S. V. (2024). Convolutional neural network models describe the encoding subspace of local circuits in auditory cortex. bioRxiv. doi: 10.1101/2024.11.07.622384
Parida, S., ..., Bartlett, E.L., Parthasarathy, A. (2024) Rapid and objective assessment of auditory temporal processing using dynamic amplitude-modulated stimuli doi: 10.1101/2024.01.28.577641
Bharadwaj, H., Parida, S., Kafi, H., Alexander, J., & Heinz, M. (2024). Overzealous Tail: Distorted Tonotopy Degrades Suprathreshold Sound Coding in Sensorineural Hearing Loss. MoH 2024, Ann Arbor, Michigan, USA. Zenodo. doi: 10.5281/zenodo.13334673
Deloche, F., Parida, S., Sivaprakasam, A. N., Heinz, M. G. (2024) Estimation of cochlear frequency selectivity using a convolution model of forward-masked compound action potentials JARO. doi: 10.1007/s10162-023-00922-1
Parida, S., Liu, S.T., & Sadagopan, S. (2023). Adaptive mechanisms facilitate robust performance in noise and in reverberation in an auditory categorization model. Commun. Biol. doi: 10.1038/s42003-023-04816-z
Sadagopan, S., Kar, M., Parida, S. (2023) Quantitative models of auditory cortical processing. Hear. Res https://doi.org/10.1016/j.heares.2023.108697
Suresh, C.H., Leng, K., Washnik, N.J. and Parida, S., (2023). The portrayal of hearing loss information in online Mandarin videos. Journal of Otology. 10.1016/j.joto.2023.05.007
Parida, S., Heinz, M.G. (2022). Underlying neural mechanisms of degraded speech intelligibility following noise-induced hearing loss: The importance of distorted tonotopy. Hear. Res. https://doi.org/10.1016/j.heares.2022.108586
Parida, S., Heinz, M.G. (2022) Distorted tonotopy severely degrades neural representations of natural speech in noise following acoustic trauma. J. Neurosci. (Featured Article) https://doi.org/10.1523/JNEUROSCI.1268-21.2021
Kar, M., Pernia, M., Williams, M., Parida, S., et al. (2022) Vocalization categorization behavior explained by a feature-based auditory categorization model. eLife. 10.7554/eLife.78278
Montes-Lourido, P., Kar, M., Pernia, M., Parida, S., Sadagopan, S. (2022) Updates to the guinea pig animal model for in-vivo auditory neuroscience in the low-frequency hearing range. Hear. Res. https://doi.org/10.1016/j.heares.2022.108603
Parida, S., Heinz, M.G. Enhanced envelope coding following acoustic trauma is detrimental to neural coding of speech in noise. bioRxiv. doi: 10.1101/2022.03.16.484675
Parida, S., Bharadwaj, H., & Heinz, M. G. (2021) Spectrally specific temporal analyses of spike-train responses to complex sounds: A unifying framework. Plos. Comp. Biol. doi: 10.1371/journal.pcbi.1008155
Parida, S., Heinz, M.G. (2021). Noninvasive measures of distorted tonotopic speech coding following noise-induced hearing loss. JARO. doi: 10.1007/s10162-020-00755-2
NWAVRM 2023. Adaptive mechanisms for robust auditory categorization in noise and reverberation
ASA 2019. Effects of noise-induced hearing loss on speech-in-noise envelope coding: Inferences from single-unit and non-invasive measures in animals. (Invited)
Parida, S. et al. (2025) Auditory cortical manifold for natural soundscapes enables neurally aligned category decoding. Cosyne/ICAC
Parida, S. et al. (2024) The cortical manifold for representation of natural soundscapes. GRC: Auditory Systems/SfN /APAN
Parida, S. et al. (2023) Rapid assessment of temporal processing from the peripheral and central auditory pathway using dynamic amplitude modulated stimuli. ARO
Parida, S., Liu, S.T., Sadagopan, S. (2022) Adaptive mechanisms for robust auditory categorization in noise and reverberation. MARC.
Parida, S., Liu, S.T., Sadagopan, S. (2021/2022) Modeling gain control mechanisms for robust auditory categorization in noise. APAN 2021/ARO 2022
Parida, S., Heinz, M.G. (2019) Effects of noise-induced hearing loss on speech-in-noise envelope coding. ARO
Parida, S., Heinz, M.G. (2018). Neurophysiological evaluation of speech masking release based on the envelope power spectrum model. ARO
Parida, S., Heinz, M.G. (2017). Neurophysiological evaluation of the speech based envelope power spectrum model. ARO
Parida, S., Pattem, A. K., & Ghosh, P. K. (2015). Estimation of the air-tissue boundaries of the vocal tract in the mid-sagittal plane from electromagnetic articulograph data. ISCA.
Parida, S. (2020). Neural representations of natural speech in a chinchilla model of noise-induced hearing loss (Doctoral dissertation, Purdue University Graduate School).
2021 Purdue College of Engineering nominee for CGS/ProQuest Distinguished Dissertation Award