What is he best known for?
The fields of study he is best known for:
- Operating system
- Database
- Internal medicine
Sherif Sakr spends much of his time researching Cloud computing, Data science, Database, Big data and RDF query language.
His Cloud computing study combines topics from a wide range of disciplines, such as Software and Provisioning.
His work on Porting as part of general Software research is frequently linked to Economies of scale, thereby connecting diverse disciplines of science.
His work on Data science is being expanded to include thematically relevant topics such as Scalability.
In his work, Cloud testing, NoSQL and Cloud computing security is strongly intertwined with Server, which is a subfield of Database.
His Big data research includes themes of Graph database, Graph, Data processing, Exploit and Analytics.
His most cited work include:
- A Survey of Large Scale Data Management Approaches in Cloud Environments (322 citations)
- Graph query processing using plurality of engines (173 citations)
- XQuery on SQL hosts (132 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Database, Cloud computing, Big data, Data science and Business process.
The various areas that Sherif Sakr examines in his Database study include RDF Schema, RDF and Cloud database.
His work in Cloud computing addresses subjects such as Distributed computing, which are connected to disciplines such as Scheduling.
His Big data research incorporates themes from Scalability, Analytics, Software engineering and SQL.
His work deals with themes such as World Wide Web and Data processing, which intersect with Data science.
His work on Business process management, Artifact-centric business process model, Business process modeling and Business process discovery is typically connected to Process management as part of general Business process study, connecting several disciplines of science.
He most often published in these fields:
- Database (23.40%)
- Cloud computing (26.42%)
- Big data (24.15%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (13.21%)
- Big data (24.15%)
- Machine learning (11.70%)
In recent papers he was focusing on the following fields of study:
Sherif Sakr mainly investigates Artificial intelligence, Big data, Machine learning, Data science and Analytics.
His work carried out in the field of Artificial intelligence brings together such families of science as Dyslipidemia and Blood pressure.
His Big data research includes elements of Data modeling, Scalability, SQL and Stream processing.
The study incorporates disciplines such as Software and Software engineering in addition to Scalability.
While the research belongs to areas of Data science, Sherif Sakr spends his time largely on the problem of Graph, intersecting his research to questions surrounding Graph and Information retrieval.
Sherif Sakr works mostly in the field of Analytics, limiting it down to topics relating to Cloud computing and, in certain cases, Distributed computing, as a part of the same area of interest.
Between 2017 and 2021, his most popular works were:
- Cardiorespiratory Fitness and Cardiovascular Disease Prevention: an Update (44 citations)
- On the interpretability of machine learning-based model for predicting hypertension (40 citations)
- RDF Data Storage and Query Processing Schemes: A Survey (40 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Database
- Internal medicine
Sherif Sakr mostly deals with Machine learning, Artificial intelligence, Data science, Big data and Scalability.
His specific area of interest is Data science, where he studies Analytics.
His work on NoSQL as part of his general Big data study is frequently connected to Benchmarking, thereby bridging the divide between different branches of science.
His studies in Scalability integrate themes in fields like Service, Set, Exploit, Software and Stream processing.
His study on Exploit is mostly dedicated to connecting different topics, such as Cloud computing.
His Software research incorporates elements of Domain and Database.
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