What is he best known for?
The fields of study he is best known for:
- Database
- Operating system
- Programming language
His main research concerns Relational database, XML database, Document Structure Description, XML Schema Editor and XML validation.
He has included themes like XML Encryption, XML, XML Signature and Efficient XML Interchange in his Relational database study.
His Efficient XML Interchange research is multidisciplinary, relying on both XML framework and XML schema.
The concepts of his XML database study are interwoven with issues in Information retrieval and Streaming XML.
Eugene J. Shekita has researched Relational database management system in several fields, including Simple API for XML, XML Schema, SQL and Data structure.
His XML Catalog research includes themes of Data model and Database design.
His most cited work include:
- Storing and querying ordered XML using a relational database system (2255 citations)
- Scaling distributed machine learning with the parameter server (846 citations)
- Improved histograms for selectivity estimation of range predicates (566 citations)
What are the main themes of his work throughout his whole career to date?
Eugene J. Shekita focuses on Information retrieval, Theoretical computer science, Database, Query optimization and Scalability.
His work carried out in the field of Information retrieval brings together such families of science as XML database, XML validation, Document Structure Description and XML Schema Editor.
His study looks at the intersection of Database and topics like Data structure with Computer data storage.
Eugene J. Shekita works mostly in the field of Query optimization, limiting it down to concerns involving Sargable and, occasionally, Query by Example.
As a member of one scientific family, he mostly works in the field of XML Encryption, focusing on XML Signature and, on occasion, XML framework.
Within one scientific family, Eugene J. Shekita focuses on topics pertaining to Database model under SQL, and may sometimes address concerns connected to Data model.
He most often published in these fields:
- Information retrieval (27.17%)
- Theoretical computer science (18.48%)
- Database (18.48%)
What were the highlights of his more recent work (between 2010-2018)?
- Scalability (16.30%)
- Distributed computing (10.87%)
- Server (6.52%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Scalability, Distributed computing, Server, Intranet and Key.
Eugene J. Shekita interconnects Replication, Compiler, Data model, Artificial intelligence and Machine learning in the investigation of issues within Scalability.
His biological study spans a wide range of topics, including Value, A* search algorithm, Open source and Data processing.
In his research, Parallel computing is intimately related to Skip list, which falls under the overarching field of Intranet.
In general Programming language study, his work on Reusability often relates to the realm of Abstraction and Schema, thereby connecting several areas of interest.
Database is closely connected to Data mining in his research, which is encompassed under the umbrella topic of Generalized linear model.
Between 2010 and 2018, his most popular works were:
- Scaling distributed machine learning with the parameter server (846 citations)
- Jaql: a scripting language for large scale semistructured data analysis (202 citations)
- Using Paxos to build a scalable, consistent, and highly available datastore (148 citations)
In his most recent research, the most cited papers focused on:
- Database
- Operating system
- Programming language
His scientific interests lie mostly in Scalability, Distributed computing, Intranet, Parallel computing and Skip list.
His work deals with themes such as Replication, Data processing and Data model, which intersect with Scalability.
His Distributed computing study integrates concerns from other disciplines, such as Consistency, Paxos, Protocol and Server.
His research integrates issues of Programming language, Compiler, JSON, Scripting language and Reusability in his study of Intranet.
His studies deal with areas such as Star schema, A* search algorithm, Analytics and Open source as well as Parallel computing.
The various areas that Eugene J. Shekita examines in his Skip list study include Scheduling and Speedup.
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