What is he best known for?
The fields of study he is best known for:
- Operating system
- Database
- Artificial intelligence
His primary areas of study are Data mining, Probabilistic logic, Wireless sensor network, Distributed computing and Query optimization.
His Data mining research includes themes of Data modeling, Database and Set.
His Probabilistic logic research incorporates themes from Probabilistic database, Graphical model, Machine learning and Optimization problem.
His Distributed computing research incorporates elements of Scalability, Cloud computing, Dataflow and Partition.
His Query optimization research integrates issues from Query expansion and Theoretical computer science.
His Query expansion study which covers Query language that intersects with Data stream mining.
His most cited work include:
- TelegraphCQ: Continuous Dataflow Processing for an Uncertain World. (1083 citations)
- Model-driven data acquisition in sensor networks (1028 citations)
- TelegraphCQ: continuous dataflow processing (607 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Data mining, Theoretical computer science, Query optimization, Database and Graph.
His Data mining research includes elements of Tuple, Wireless sensor network, Inference, Graphical model and Probabilistic logic.
His biological study spans a wide range of topics, including Probabilistic database, Machine learning, Uncertain data and Time complexity.
His work carried out in the field of Query optimization brings together such families of science as Query language, Query expansion, Data stream mining and Distributed computing.
His Database research is multidisciplinary, incorporating elements of Information extraction and Markov chain.
Amol Deshpande has included themes like Graph and Analytics in his Graph study.
He most often published in these fields:
- Data mining (28.31%)
- Theoretical computer science (25.30%)
- Query optimization (18.67%)
What were the highlights of his more recent work (between 2016-2021)?
- Data science (12.05%)
- Data management (12.05%)
- Theoretical computer science (25.30%)
In recent papers he was focusing on the following fields of study:
Amol Deshpande focuses on Data science, Data management, Theoretical computer science, Graph and Graph.
Within one scientific family, Amol Deshpande focuses on topics pertaining to Metadata under Data science, and may sometimes address concerns connected to Query language, Approximation algorithm, Automatic summarization, Vertex and Segmentation.
Data management is a subfield of Database that he studies.
The concepts of his Theoretical computer science study are interwoven with issues in Relational database, Data mining and Hash function.
Amol Deshpande interconnects Crowdsourcing, Intersection, Query expansion and Leverage in the investigation of issues within Data mining.
His research in Graph focuses on subjects like Data modeling, which are connected to RDF.
Between 2016 and 2021, his most popular works were:
- Towards Unified Data and Lifecycle Management for Deep Learning (49 citations)
- Big Graph Analytics Platforms (39 citations)
- ModelHub: Deep Learning Lifecycle Management (37 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Artificial intelligence
- Database
Amol Deshpande mostly deals with Application lifecycle management, Data management, Data science, Graph and Software engineering.
His Data management study combines topics in areas such as Query expansion, Heuristics and Query optimization.
The Graph study combines topics in areas such as Relational database, Analytics and Graph.
His research investigates the connection between Analytics and topics such as Relational database management system that intersect with issues in Theoretical computer science and Graph database.
He has researched Artificial intelligence in several fields, including Data modeling, Machine learning, SQL and Domain-specific language.
His Graph rewriting study frequently links to related topics such as Data mining.
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