What is he best known for?
The fields of study he is best known for:
- Operating system
- Programming language
- Central processing unit
Rajesh Bordawekar mainly focuses on Parallel computing, Operating system, Passion, Input/output and Java.
His Parallel I/O study, which is part of a larger body of work in Parallel computing, is frequently linked to Function, bridging the gap between disciplines.
His research on Operating system frequently links to adjacent areas such as Heap.
His biological study spans a wide range of topics, including Software and Scalability.
His work carried out in the field of Java brings together such families of science as Dead code elimination, Pointer and Memory management.
In general Programming language study, his work on Programming paradigm, High-level programming language, Second-generation programming language and Fifth-generation programming language often relates to the realm of Programming domain, thereby connecting several areas of interest.
His most cited work include:
- Improved parallel I/O via a two-phase run-time access strategy (219 citations)
- Passion: Optimized I/O for Parallel Applications (122 citations)
- Passion: Optimized I/O for Parallel Applications (122 citations)
What are the main themes of his work throughout his whole career to date?
Parallel computing, Programming language, Compiler, Theoretical computer science and Artificial intelligence are his primary areas of study.
His Parallel computing research is multidisciplinary, incorporating perspectives in Scalability and Computation.
His study ties his expertise on Streaming XML together with the subject of Programming language.
His Compiler research includes elements of Fifth-generation programming language and Programming paradigm.
His Theoretical computer science study combines topics in areas such as Algorithm, Graph and Data structure.
His Artificial intelligence study integrates concerns from other disciplines, such as Relational database, Speech recognition and Natural language processing.
He most often published in these fields:
- Parallel computing (33.98%)
- Programming language (18.45%)
- Compiler (12.62%)
What were the highlights of his more recent work (between 2014-2021)?
- Artificial intelligence (9.71%)
- Word embedding (5.83%)
- Relational database (5.83%)
In recent papers he was focusing on the following fields of study:
Rajesh Bordawekar spends much of his time researching Artificial intelligence, Word embedding, Relational database, Natural language processing and Theoretical computer science.
His study in Artificial intelligence is interdisciplinary in nature, drawing from both Speech recognition and Data science.
In Word embedding, Rajesh Bordawekar works on issues like Information retrieval, which are connected to Private information retrieval and Encoding.
The various areas that he examines in his Natural language processing study include Word and Set.
The concepts of his Theoretical computer science study are interwoven with issues in Algorithm, Graph and Data structure.
His work deals with themes such as Counting sort, Proxmap sort, Radix sort and Parallel computing, which intersect with Data set.
Between 2014 and 2021, his most popular works were:
- PARADIS: an efficient parallel algorithm for in-place radix sort (24 citations)
- Using Word Embedding to Enable Semantic Queries in Relational Databases (20 citations)
- Concept Analysis Operations Utilizing Accelerators (18 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Programming language
- Database
Rajesh Bordawekar mostly deals with Data structure, Theoretical computer science, Matrix representation, Analytics and SQL.
His Theoretical computer science study combines topics from a wide range of disciplines, such as Graph, Representation and Computer hardware.
His work carried out in the field of Matrix representation brings together such families of science as Sparse matrix and Matrix multiplication.
The study incorporates disciplines such as Data type, Key and Implementation in addition to Analytics.
His studies deal with areas such as Relational database, Artificial intelligence and Word embedding as well as SQL.
The Word embedding study combines topics in areas such as Inductive reasoning, Conjunctive query, Data model and Natural language processing.
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