Imagine if there was a revolutionary wearable technology that could enable the user to open doors or operate machinery with a simple wave of their hand or a mere blink of their eye? What people might not realize is that this contact-free human-machine technology already exists—and it has been developed right here in a laboratory at KAUST.
KAUST master's degree student José Ilton de Oliveira Filho recently won first place at the second edition of the IEEE International Sensors and Measurement Systems Student Contest (IEEE IS&M-SC). IEEE IS&M-SC is a global competition directed at teams of advanced undergraduates, master's degree and Ph.D. students and seeks to stimulate creative ideas for sensor and measuring systems applications.

Abdulaziz Alhoshany, et al., "A Precision, Energy-Efficient, Oversampling, Noise-Shaping Differential SAR Capacitance-to-Digital Converter" IEEE Transactions on Instrumentation and Measurement, 68 (2), 2019, 392.

Elgammal, M. A., Mostafa, H., Salama, K. N., & Mohieldin, A. N. (2019, August). A Comparison of Artificial Neural Network (ANN) and Support Vector Machine (SVM) Classifiers for Neural Seizure Detection. In 2019 IEEE 62nd International Midwest Symposium on Circuits and Systems (MWSCAS) (pp. 646-649). IEEE.

The present study describes the one-step synthesis of NiO nanosheets and successful surface modification of NiO nanosheets with Au NPs. This surface modification step is vital for an application (i.e., hydrazine sensing), where Au NPs enhance the surface area and provide synergistic effect during the electrocatalytic reaction.