Reem Shadid

Affiliation

Elect. Eng. Dept., Applied Science Private University, Amman, Jordan

Topic

Amount Of Charge,Charge Movement,Convolutional Neural Network,Deep Learning,Deep Neural Network,Discontinuity Point,Electric Charge,Electrostatic Interactions,Long Short-term Memory,Magnetic Field,Magnetic Force,Maxwell’s Equations,Negatively Charged,Neural Network,Output Layer,Points In Space,Positively Charged,Power System,Recurrent Neural Network,Side Surface,Static Electric Field,AC State,AC State Estimation,Activation Function,Additive Noise,Ampere’s Law,Basis For Further Exploration,Biot-Savart,Calibrated Model Parameters,Calibration Approach,Calibration Method,Changes In Position,Changes In Space,Changes In Speed,Charge Density,Charge Flow,Constant Speed,Convolutional Neural Network Model,Current Flow,Decoder Part,Deep Learning Architectures,Denoising Autoencoder,Dense Layer,Device Model,Direct Elements,Direction Of Force,Dynamic Response,Electric Interaction,Electromagnetic Field,Electromagnetic Interaction,

Biography

Reem Shadid received the B.Sc. and M.Sc. degrees in electrical engineering from The University of Jordan, in 2003 and 2015, respectively, and the Ph.D. degree in electrical engineering from the University of North Dakota, Grand Forks, ND, USA, in 2018. She is currently an Assistant Professor with the Department of Electrical Engineering, Applied Science Private University. Her research interests include electromagnetic theory, electromagnetic waves, power systems, power control and stability, and wireless power transfer.