Perception of complex natural scenes, with a special focus on hearing and audiovisual integration; Intuitive physics and causal reasoning; Constructing and testing models that "hear the world like humans" with generative models, probabilistic inference, statistical signal processing, and machine learning; Theoretical models of biological information processing, with a special focus on auditory perception; Biologically inspired technologies to aid the hearing-impaired.
J. Traer, M. Cusimano, and J.H. McDermott, “A perceptually inspired generative model of rigid-body contact sounds”, Digital Audio Effects (DAFx), (2019 – in press; conference paper).
M.J. Bianco, P. Gerstoft, E. Ozanich,M. A. Roch, S. Gannot, C.-A. Deledalle, J. Traer and W. Li, “Machine learning in acoustics: a review”, J. Acous. Soc. Am., (2019 – in press).
J. Traer, and J.H. McDermott, “Intuitive Physical Inference from Sound”, Comp. Cog. Neuro., (2018; conference paper).
K. J. P. Woods, M. H. Siegel, J. Traer and J. H. McDermott, “Headphone screening to facilitate web-based auditory experiments”, Atten., Percep., Psych., (2017).
Z. Zhang, J. Wu, Q. Li, Z. Huang, J. Traer, J.H. McDermott, J.B. Tenenbaum, and W.T. Freeman, “Generative Modeling of Audible Shapes for Object Perception”, ICCV, (2017; conference paper).