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Abdelkader Baggag
Affiliation
Qatar Computing Research Institute, HBKU
Topic
2D Space,Agglomerative Clustering,Automatic Techniques,Autoregressive Model,Basic Tasks,Black Dots,Blue Spheres,Chart Types,Class Separation,Clustering Patterns,Clustering Techniques,Complex Patterns,Confusion Matrix,Counting Task,Crowdsourcing,DBSCAN Clustering,Data Space,Decision Boundary,Design Techniques,Dimensional Space,Directed Graph,Exploratory Analysis,Extensive Experiments,Gaussian Mixture Model,Good Clustering,Graphical Representation,Green Spheres,Homology Groups,Horizon,Human Evaluation,Human Subjects,Intelligent Transportation Systems,Lack Of Ground Truth,Latent Space,Linear Discriminant Analysis,Linearly Separable,Mathematical Framework,Matrix Factorization,Mean Absolute Percentage Error,Missing Values,Mixture Model,Multidimensional Data,Pair Of Classes,Paired Plots,Parameter Space,Performance Measurement Systems,Polyline,Quality Metrics,Red Spheres,Red Spots,
Biography
Abdelkader Baggag is a senior scientist with the Qatar Computing Research Institute, and an associate professor of data science at Hamad Bin Khalifa University, where he teaches advanced Machine Learning. His research focuses on developing data-driven models for finding patterns in complex data (mobility and health data) and implementing these methods in high-performance solutions, in particular multidimensional data and sequence of states data to support domain experts in traffic using sensors data, and eHealth for analyzing large-scale wearable sensor signals. His expertise is machine learning, representation learning, temporal causal modeling, artificial intelligence for health and mobility analytics, and missing data imputation.