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Nadeem Javaid
Also published under:N. Javaid
Affiliation
ComSens Laboratory, International Graduate School of Artificial Intelligence, National Yunlin University of Science and Technology, Yunlin, Taiwan
Topic
Deep Learning Models,Convolutional Neural Network,Long Short-term Memory,SHapley Additive exPlanations,Convolutional Layers,Model Performance,SHapley Additive exPlanations Values,Explainable Artificial Intelligence,Hybrid Model,Individual Models,Internet Of Things,Learning Algorithms,Machine Learning Techniques,Minority Class,Performance Metrics,Prediction Accuracy,Support Vector Machine,Synthetic Minority Oversampling Technique,Artificial Neural Network,Balancing Techniques,Cardiovascular Disease,Consensus Mechanism,Contribution Of Features,Feature Selection Techniques,Gated Recurrent Unit,Gradient Boosting,Inception Module,Internet Of Things Devices,Machine Learning Models,Minority Class Samples,Missing Values,Neural Network,Oversampling Technique,Recurrent Neural Network,Root Mean Square Error,Smart Contracts,Base Layer,Cost Prediction,Cryptocurrencies,Data Security,Data Storage,Deep Learning,Deep Learning Techniques,Deep Models,Deep Neural Network,Echo State Network,Ensemble Approach,Ensemble Model,Extreme Gradient Boosting,Fully-connected Layer,
Biography
Nadeem Javaid (S’8–M’11–SM’16) received the master’s degree in electronics from Quid-I-Azam University, Islamabad, Pakistan, in 1999, and the Ph.D. degree from the University of Paris-Est, France, in 2010. He is currently an Associate Professor and the founding Head of ComSens (Communications over Sensors) Research Group, Department of Computer Science, COMSATS Institute of Information Technology, Islamabad, Pakistan. He has supervised seven Ph.D. and 70 M.S. theses. He has authored over 450 papers in technical journals and international conferences. He is also an Associate Editor of the IEEE Access Journal and an Editor of the International Journal of Space-Based and Situated Computing. His research interests include wireless ad hoc networks, wireless sensor networks, and energy optimization in smart grids.