Mai Abdelhakim

Affiliation

Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, USA

Topic

Deep Learning,Distribution System,Edge Of The Grid,Loading Control,Machine Learning,Secondary Cell,Unsupervised Learning,Validation Set,730 Days,Access Control,Access Control Policies,Access Request,Accuracy Of Model,Adoption Rate,Advertising,All-to-all Communication,Anonymous Identification,App Use,Arrival Rate,Attack Detection,Attribute-based Access Control,Attribute-based Access Control Policy,Bandwidth Allocation,Bluetooth Low Energy,Close Contact,Communication Network,Complex Policy,Contact Duration,Contact Tracing,Customer Value,Daily Reports,Daily Values,Data Privacy,Deep Reinforcement Learning,Deep Reinforcement Learning Agent,Detection Accuracy,Detection Performance,Device Placement,Direct Contact,Distributed Energy Resources,Distribution Network,Electric Vehicles,Electricity Theft,Energy Conservation,Energy Consumption,Energy Consumption Data,Energy Distribution,Energy Meter,Energy Use,Excess Energy,

Biography

Mai Abdelhakim received the B.Sc. and M.Sc. degrees in communications engineering from Cairo University in 2006 and 2009, respectively. She is currently a Graduate Research Assistant with the Electrical and Computer Engineering Department, Michigan State University, where she is currently pursuing the Ph.D. degree. Her current research focuses on reliable and efficient communications in sensor networks and high-speed wireless networks.