Mounya Elhilali, founder of the Department of Electrical and Computer Engineering’s Laboratory for Computational Audio Perception (LCAP), is recognized for advancing the understanding of how the human brain and machines process the complexities of sound.
Elhilali’s research bridges the gap between neuroscience and audio technologies by examining the computational and neural bases of sound and speech perception and behavior in complex acoustic environments. Using mathematical signal processing models, behavioral testing (psychoacoustics), and neural recordings, she focuses on decoding how these processes guide human behavior, and on engineering more efficient machine parsing of complex soundscapes. Her work has applications in a wide range of fields spanning the medical, commercial, military, and robotic domains.
Recently, Elhilali has explored how attention to sound provides feedback to brain networks and changes how humans analyze and understand their acoustic surroundings. The brain operates as an adaptive system that constantly changes its processing in order to sift through the cacophony of sounds in our environments. By studying and modeling this adaptive behavior, Elhilali’s work offers novel theories for advancing intelligent audio technologies. Her multidisciplinary research is creating a number of insights into brain sciences, adaptive signal processing, audio technologies, and medical systems, including devising new diagnosis technologies that leverage body sounds to tackle public health problems, such as pneumonia, that affect millions worldwide.
Affiliated with Johns Hopkins’ Center for Language and Speech Processing, Elhilali is a member of Institute of Electrical and Electronic Engineers (IEEE, senior member), IEEE Signal Processing Society, Acoustical Society of America (ASA), Society for Neuroscience (SfN), Association for Research in Otolaryngology (ARO), International Speech Communication Association (ISCA), Association for Women in Science (AWIS), and the American Society for Engineering Education (ASEE). The recipient of Johns Hopkins University Catalyst Award (2017) and Kenan Award for Innovative Projects in Undergraduate Education (2015), she won the prestigious Office of Naval Research Young Investigator Award and a National Science Foundation Early Career Award. She is a member of the IEEE speech and language processing technical committee and the IEEE research and development policy committee and serves on the technical committee of many conferences and the editorial boards of various publications, including Neural Networks, PLOS Computational Biology and Frontiers in Neuroscience.
She received her BS in Software Engineering from Al Akhawayn University (Ifrane, Morocco) in 1998 and an MS (2003) and PhD (2004) in Electrical and Computer Engineering from the University of Maryland.