ABDULILAH MOHAMMAD Mayet
King Khalid University, SEMC, King Abdullah University of Science and Technology, King Fahd University of Petroleum and Minerals
Research areas: Engineering · Electrical and Electronic Engineering · Flow Measurement and Analysis · Non-Destructive Testing Techniques · Nuclear Physics and Applications
0000-0001-7739-0105
About
Currently, he is an assistant professor at King Khalid University, teaching courses in Nanofabrication and FPGA for AI. He is also the director of the engineering college research center and consultant at the artificial intelligence center (AIC). He has joined King Abdullah University of science and technology (KAUST) and got his master's and doctoral degrees in electrical engineering in the field of microelectronics. He had a co-advisor from Cornell University. He earned his bachelor's degree from King Fahd University of Petroleum and Minerals (FUPM). He has research collaboration with the University of California Irvine and Cornell University.
His doctoral research focused on innovating and fabricating new fully amorphous metal (patented) to fabricate nanoscale MEMS devices (NEMS). He had done the proof of concept, designed, simulated, and fabricated multiple devices, then tested them during his PhD research. He was designated as the CTO for SEMC company, manufacturing high industrial spec inertial sensors and bolometers. He managed and mentored a highly qualified engineering team to do the proof of concept hardware, qualifications procedures, and critical performance. We have fabricated multiple kinds of MEMS-based sensors. He has rich knowledge and experience in fabricating MEMS-based inertial sensors and micro-bolometers. He has attended various advanced management, leading, innovation, strategic planning, and entrepreneur courses at MIT, Cornell, and IE universities, which shaped my knowledge and experience.
Before his PhD study, he spent ten years in the nano-fabrication field as system engineering and conducted extensive training at ETEC and ATMEL-ES2 for semiconductor fabrication. He has also accumulated in-depth knowledge and expertise in entrepreneurship, management, and products development. He started a commercial manufacturing company from scratch and held the CEO position. He spent five years in ARAMCO.
Employment
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King Khalid University Professor2019 - Present
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SEMC CTO2016 - 2019
Education
- 2011 - 2016
- 2010 - 2011
- 1987 - 1991
Projects & Funding
Projects & funding information is unavailable.
Publications (85)
- High-gain dual antenna microwave sensor to accurate determination of water content in crude oil using GMDH neural network Save
- Correction: Mayet et al. Experimental Analysis to Detect Corona COVID-19 Virus Symptoms in Male Patients Through Breath Pattern Using Machine Learning Algorithms. Electronics 2023, 12, 10 Save
- Accurate X-ray-based thickness determination of aluminum sheets using ACO-optimized MLP neural networks Save
- Accurate three-phase flow measurement in scale-lined pipelines: A hybrid SSA and XGBoost approach Save
- Efficient Multiplierless FPGA Architecture for Brain-Inspired Rulkov Neuron Mapping Save
- Fluid-independent volume fraction measurement in liquid-gas flow using tomographic data and deep neural networks Save
- From nonlinear neuronal dynamics to AI-optimized VLSI hardware: multiplier-free FPGA implementation of memristive FN-HR coupled neural networks for intelligent systems Save
- Global Renewable Energy Forecasting Using Hybrid Deep Learning and Two-Tier Optimization Models Save
- High accuracy EEG signal classification for brain computer interfaces using advanced neural architectures Save
- Nonlinear Hopf-based cochlear network: Bio-inspired modeling, analysis, and FPGA implementation for cochlear implant applications Save
- Nonlinear analysis and multiplier-free digital realization of a modified 4D Wilson neural model for real-time neuromorphic applications Save
- Nonlinear hardware realization and fast digital approximation of the dressed neuron model for astrocyte–neuron coupling dynamics Save
- Novel application of COMBI learning models and multi-objective Lichtenberg algorithm in HVAC system design Save
- Pareto-optimal design of integrated solar–geothermal energy systems using an intelligent hybrid optimization and decision-making approach Save
- Radiation-based non-invasive prediction of scale thickness in oil pipelines using autoregressive modeling and k-nearest neighbors regression algorithm Save
- Scale-dependent simulation of nonlocal dual-phase-lag thermoelastic dissipation and frequency shift in circular nanoplate resonators via the frequency-based method Save
- A microstrip-based sensor for glucose monitoring: towards non-invasive blood glucose detection Save
- A novel approach for measuring the void fraction in stratified air-water systems utilizing an 8-blade capacitance-based sensor, sinogram, and a deep neural network Save
- ACO-based feature selection and neural network modeling for accurate gamma-radiation based pipeline monitoring in the oil industry Save
- An investigation on inner ear operation in sense of hearing: High-speed FPGA-based circuits for digital realization of 2D cochlea modeling Save