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SpatialHadoop: SpatialHadoop is an open-source MapReduce extension for Apache Hadoop framework with built-in support for spatial data. It employs the MapReduce programming paradigm for distributed processing to build a general purpose tool for large scale analysis of spatial data on large clusters. My role is to design, implement and evaluate innovative research ideas to extend the current features of SpatialHadoop.

Organizations: University of Minnesota.

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DFP Localization: Device-free Passive (DFP) localization in WLANs has been introduced as a value-added service that allows tracking of indoor entities that do not carry any devices. My role was to provide accurate and effective multi-entity detection and tracking by investigating recent wireless technologies combined with solid machine learning techniques.

Organizations: Egypt-Japan University of Science and Technology and Alexandria University.

Publications: [TMC'14] [WCNC'13] [GLobCom'12] [Demo].

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Microsoft Collaborative Translation Platform: It is required in this project to provide a scalable platform to work as web service for Microsoft Traslator Hub that serves requests for public translation and private ones. This platform allows the community managers, translators and reviewers to collect content and adjust translations with the assistance of professional translators. My mission was to propose and develop a system that integrates automated evaluation where human evaluation target eventually granting degrees minutes for level translating content. The proposed system should consider the different levels of translations produced by translators and systems.

Organizations: Microsoft Research.

Publications: [My M.Sc. Thesis] [MS Middle East News].

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Wiki-Rec Recommendation: The usage of semantic-based analysis has gained much interest in recent years. The emergence of ontologies has yet facilitated semantic interpretation of text. However, relying on an ontology for performing the semantic analysis requires too much effort to construct and maintain the used ontologies. Besides, the currently known ontologies cover a small number of the world's concepts especially when non-domain-specific concepts are needed. The focus of this project is to propose the use of Wikipedia as ontology to solve the problems of using traditional ontologies for the text analysis in text-based recommendation systems. My mission was to develop a novel approach to construct an ontology from wikipedia categories and articles graphs. Moreover, it was required to propose an efficient structure for users profiles to integrate smoothly with the built ontology.

Organizations: Alexandria University.

Publications: [ISDA'10].