Prof. Dr. Verhulst is Associate Professor in Hearing Technology at the Faculty of Engineering and Architecture, and joined Ghent University in 2016 after PhD and post- doctoral training at the Technical University of Denmark, Boston University and Harvard Medical school. Her lab consists of 6 members working interdisciplinary (combining EEG, sound perception, machine learning and computational neuroscience) on the topics of machine hearing and advanced (AI-based) hearing diagnostics and restoration methods. She has organized the international auditory modeling and speech-in-noise workshops, is a technical committee member of the acoustical society of America and received the 2016 Niedersachsen Wissenschaftspreis (Kat.II) as well as the 2018 Advances and Perspectives in Auditory Neuroscience (APAN) Young Investigator Spotlight Prize.
Keywords: Auditory neuroscience, machine hearing, auditory modeling, hearing loss, hearing technology
Baby D. and Verhulst S (2018). Biophysically-inspired features improve the generalizability of neural network-based speech enhancement systems. Interspeech, Hyderabad, India (5 pages).
Baby D. and Verhulst S (preprint, 2018) Machines hear better when they have ears arXiv preprint arXiv:1806.01145.
Verhulst S, Altoè A, Vasilkov V. (2018) Computational modeling of the human auditory periphery: auditory-nerve responses, evoked potentials and hearing loss. Hearing Research, 360, 55-75.
Saremi A, Beutelmann R, Dietz M, Kretzberg J, Ashida A, Verhulst S (2016) Comparative Study of Seven Auditory Filter Models of the Human Cochlea. Journal of the Acoustical Society of America 140 (3), 1618-1634.
Verhulst S, Bharadwaj H, Mehraei G, Shera CA, Shinn-Cunningham, BG. (2015). Functional modeling of the human auditory brainstem response to broadband stimulation. Journal of the Acoustical Society of America 138 (3): 1637-1659.