What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Operating system
- Database
His primary areas of study are Data mining, Probabilistic logic, Uncertain data, Database and Search engine indexing.
His study in the fields of Probabilistic database and Query language under the domain of Data mining overlaps with other disciplines such as Spatial query.
His Probabilistic logic research is multidisciplinary, incorporating perspectives in Range query, Information retrieval and Categorical variable.
He combines subjects such as Probability density function, Theoretical computer science and Pruning with his study of Uncertain data.
His studies deal with areas such as Computer security and Real-time computing as well as Database.
His Search engine indexing study incorporates themes from Object, Scalability and Data structure.
His most cited work include:
- Evaluating probabilistic queries over imprecise data (565 citations)
- Querying imprecise data in moving object environments (401 citations)
- Query indexing and velocity constrained indexing: scalable techniques for continuous queries on moving objects (336 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Data mining, Database, Theoretical computer science, Search engine indexing and Probabilistic logic.
In the field of Data mining, his study on Uncertain data and Probabilistic database overlaps with subjects such as Tuple.
His Uncertain data research includes themes of Database model and Pruning.
The concepts of his Database study are interwoven with issues in Computer security, Distributed computing and Information retrieval.
His Theoretical computer science research is multidisciplinary, incorporating elements of Range, Sort-merge join, Join and Steganography.
His research in Search engine indexing intersects with topics in Tree, Object, Scalability and Overhead.
He most often published in these fields:
- Data mining (38.67%)
- Database (25.33%)
- Theoretical computer science (16.00%)
What were the highlights of his more recent work (between 2011-2020)?
- Database (25.33%)
- Data mining (38.67%)
- Cloud computing (3.33%)
In recent papers he was focusing on the following fields of study:
Sunil Prabhakar focuses on Database, Data mining, Cloud computing, Information retrieval and Conflict resolution.
His Database research includes elements of Range, Trie, Longest common subsequence problem and Bitmap.
While working in this field, Sunil Prabhakar studies both Data mining and Subsequence.
Sunil Prabhakar has included themes like Computer security and The Internet in his Cloud computing study.
His research in Information retrieval intersects with topics in Sentence and Data management.
The concepts of his Scalability study are interwoven with issues in Paragraph, Distributed computing, Search engine indexing and Data aggregator.
Between 2011 and 2020, his most popular works were:
- Trustworthy data from untrusted databases (21 citations)
- System and methods for ensuring integrity, authenticity, indemnity, and assured provenance for untrusted, outsourced, or cloud databases (15 citations)
- Sequential pattern mining in databases with temporal uncertainty (13 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Database
His primary scientific interests are in Database, Cloud computing, Data mining, Scalability and Homophily.
His studies in Database integrate themes in fields like Granularity, Artificial intelligence, Synchronization, Event and Machine learning.
Sunil Prabhakar has included themes like Computer security, Control, Database server and Service in his Cloud computing study.
His Data mining study combines topics in areas such as Wireless sensor network, Leverage and Sensor fusion.
The study incorporates disciplines such as Data stream mining, Throughput, Search engine indexing and Search algorithm in addition to Scalability.
The various areas that Sunil Prabhakar examines in his Homophily study include Graph, Theoretical computer science, Embedding, Network embedding and Forcing.
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