Malek Itani

CSE 314

185 E Stevens Way NE

Seattle, WA 98195

Current Electrical Engineering PhD student at the University of Washington in Seattle. Research Assistant in the Mobile Intelligence Lab working with Prof. Shyam Gollakota in the Paul G. Allen School for Computer Science & Engineering.

My current research interests lie broadly in the areas of mobile systems, embedded systems, machine learning, audio & speech, and small-scale robotics. I am committed to exploring innovative intersections among these fields to drive impactful advancements.

I received my bachelor’s in Electrical and Computer Engineering from the American University of Beirut while working with Prof. Joseph Costantine at the Electromagnetics Lab.

Selected Publications

2023

Real-Time Target Sound Extraction

Bandhav Veluri, Justin Chan, Malek Itani, and 3 more authors

In ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023
Wireless Earbuds for Low-Cost Hearing Screening

Justin Chan, Antonio Glenn, Malek Itani, and 5 more authors

In Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services, 2023

Abs

We present the first wireless earbud hardware that can perform hearing screening by detecting otoacoustic emissions. The conventional wisdom has been that detecting otoacoustic emissions, which are the faint sounds generated by the cochlea, requires sensitive and expensive acoustic hardware. Thus, medical devices for hearing screening cost thousands of dollars and are inaccessible in low and middle income countries. We show that by designing wireless ear-buds using low-cost acoustic hardware and combining them with wireless sensing algorithms, we can reliably identify otoacoustic emissions and perform hearing screening. Our algorithms combine frequency modulated chirps with wideband pulses emitted from a low-cost speaker to reliably separate otoacoustic emissions from in-ear reflections and echoes. We conducted a clinical study with 50 ears across two healthcare sites. Our study shows that the low-cost earbuds detect hearing loss with 100% sensitivity and 89.7% specificity, which is comparable to the performance of a $8000 medical device. By developing low-cost and open-source wearable technology, our work may help address global health inequities in hearing screening by democratizing these medical devices.Open-source hardware and code can be found here: https://github.com/uw-x/OAEbuds