Topic
- Computing and Processing
- Components, Circuits, Devices and Systems
- Communication, Networking and Broadcast Technologies
- Power, Energy and Industry Applications
- Signal Processing and Analysis
- Robotics and Control Systems
- General Topics for Engineers
- Fields, Waves and Electromagnetics
- Engineered Materials, Dielectrics and Plasmas
- Bioengineering
- Transportation
- Photonics and Electrooptics
- Engineering Profession
- Aerospace
- Geoscience
- Nuclear Engineering
- Career Development
- Emerging Technologies
- Telecommunications
- English for Technical Professionals
Nadra Guizani
Affiliation
Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, USA
Topic
Internet Of Things,Deep Learning,Internet Of Things Applications,Internet Of Things Devices,Data Transmission,Edge Computing,Energy Consumption,Internet Of Vehicles,Mobile Edge Computing,Mobile Network,Smart City,Task Offloading,6G Networks,Achievable Rate,Adaptive Beamforming,Antenna Array,Automatic Identification System,Autonomous Surface Vehicles,Autonomous Vehicles,Average Cost,Average Energy Consumption,Base Station,Beamforming Vector,Benign Tumors,Blockchain,Breast Tumors,Cache Hit,Carrier Frequency,Central Entity,Cloud Providers,Coalition Formation,Communication Protocol,Communication Range,Computational Overhead,Computational Resources,Computed Tomography,Computer-aided Diagnosis,Convolutional Layers,Convolutional Network,Convolutional Neural Network,Convolutional Neural Network Architecture,Convolutional Neural Network Model,Cross-entropy Loss,Data Delivery,Data Packets,Decision Network,Deep Neural Network,Delay Increases,Deterministic,Digital Twin,
Biography
Nadra Guizani (Member, IEEE) received the Ph.D. degree from Purdue University in 2020. She is an Assistant Professor with the Department of Computer Science and Engineering, The University of Texas at Arlington. Her research areas include data analytics, artificial intelligence, blockchain, cybersecurity, network function virtualization, and machine learning in engineering education. She is an Active Member in ACM and Computing Research Association.