World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
31
Citations
3267
World Ranking
13765
National Ranking
5467

Research.com Recognitions

  • 2017 - European Association for Theoretical Computer Science (EATCS) Fellow For major contributions to algorithms, the uses of randomisation in algorithms, randomness in networks, and the real-world applications of these topics

Overview

What is he best known for?

The fields of study he is best known for:

  • Programming language
  • Database
  • Operating system

His primary areas of study are Data stream management system, Operator, Relation, Class and Complex event processing. Many of his studies involve connections with topics such as Theoretical computer science and Data stream management system. Anand Srinivasan studied Operator and Distributed computing that intersect with Execution plan, State information and Process.

His Relation research incorporates elements of Timestamp, Real-time computing and State. Anand Srinivasan has included themes like Regular expression, Data stream mining, Data mining and Pattern matching in his Class study. His Complex event processing study deals with Database intersecting with World Wide Web.

His most cited work include:

  • Adding new continuous queries to a data stream management system operating on existing queries (102 citations)
  • Standardized database connectivity support for an event processing server (78 citations)
  • Support for user defined functions in a data stream management system (76 citations)

What are the main themes of his work throughout his whole career to date?

His scientific interests lie mostly in Database, Complex event processing, Data mining, Query optimization and Real-time computing. Anand Srinivasan has researched Database in several fields, including World Wide Web and Set. His Complex event processing research integrates issues from Extensibility, Data type, Parsing and Parameterized complexity.

His work in Data mining addresses issues such as Pattern matching, which are connected to fields such as Pattern recognition, Data stream mining and Dynamic data. His studies deal with areas such as Window and Event stream as well as Real-time computing. The Window study combines topics in areas such as Value, Process and Data stream management system.

He most often published in these fields:

  • Database (25.00%)
  • Complex event processing (25.00%)
  • Data mining (23.08%)

What were the highlights of his more recent work (between 2012-2015)?

  • Query optimization (21.15%)
  • Information retrieval (17.31%)
  • Data mining (23.08%)

In recent papers he was focusing on the following fields of study:

The scientist’s investigation covers issues in Query optimization, Information retrieval, Data mining, Sargable and Query plan. In general Data mining, his work in Data stream mining is often linked to Data records and Multiple input linking many areas of study. His research in Event is mostly concerned with Complex event processing.

His Inheritance research includes themes of Real-time computing and Event stream. His Database study incorporates themes from World Wide Web and Event data. The study incorporates disciplines such as Window, Value and Dimension in addition to Relation.

Between 2012 and 2015, his most popular works were:

  • Variable duration non-event pattern matching (66 citations)
  • Real-time business event analysis and monitoring (55 citations)
  • Hybrid execution of continuous and scheduled queries (52 citations)

In his most recent research, the most cited papers focused on:

  • Programming language
  • Database
  • Operating system

Anand Srinivasan spends much of his time researching Event stream, Database, Real-time computing, Sargable and Query optimization. His Event stream study frequently draws connections between adjacent fields such as Variable. His study in the field of Relational database and Business intelligence also crosses realms of Streaming data, Second source and Event analysis.

His work deals with themes such as Complex event processing, Distributed computing and STREAMS, which intersect with Real-time computing. His study on Sargable is intertwined with other disciplines of science such as Join, Event, Information retrieval and Relation. Anand Srinivasan performs multidisciplinary study on Query optimization and Query plan in his works.

Best Publications

  • Configurable data windows for archived relations

    Unmesh Anil Deshmukh;Anand Srinivasan;Sandeep Bishnoi

  • Techniques for matching a certain class of regular expression-based patterns in data streams

    Anand Srinivasan;Rakesh Komuravelli;Namit Jain;Shailendra Mishra

  • Adding new continuous queries to a data stream management system operating on existing queries

    Namit Jain;Anand Srinivasan;Shailendra Kumar Mishra

  • Join operations for continuous queries over archived views

    Unmesh Anil Deshmukh;Anand Srinivasan;Vikram Shukla;Prathab Kali

  • Support for user defined functions in a data stream management system

    Anand Srinivasan;Namit Jain;Shailendra Kumar Mishra

  • Standardized database connectivity support for an event processing server

    Mohit Thatte;Sandeep Bishnoi;Namit Jain;Anand Srinivasan

  • Framework for dynamically generating tuple and page classes

    Hoyong Park;Namit Jain;Anand Srinivasan;Shailendra Mishra

  • Dynamically sharing a subtree of operators in a data stream management system operating on existing queries

    Namit Jain;Anand Srinivasan;Shailendra Kumar Mishra

  • Variable duration non-event pattern matching

    Unmesh Anil Deshmukh;Anand Srinivasan

  • Handling Silent Relations In A Data Stream Management System

    Namit Jain;Anand Srinivasan;Shailendra Kumar Mishra

  • Method to create a partition-by time/tuple-based window in an event processing service

    Hoyong Park;Namit Jain;Anand Srinivasan;Shailendra Mishra

  • Support for sharing computation between aggregations in a data stream management system

    Anand Srinivasan;Namit Jain;Shailendra Kumar Mishra

  • Support for user defined aggregations in a data stream management system

    Anand Srinivasan;Namit Jain;Shailendra Kumar Mishra

  • Standardized database connectivity support for an event processing server in an embedded context

    Mohit Thatte;Sandeep Bishnoi;Namit Jain;Anand Srinivasan

  • Support for a parameterized query/view in complex event processing

    Parul Jain;Vikram Shukla;Anand Srinivasan;Alexandre de Castro Alves

  • Infrastructure for spilling pages to a persistent store

    Hoyong Park;Namit Jain;Anand Srinivasan;Shailendra Mishra

  • Spatial data cartridge for event processing systems

    Hoyong Park;Alexandre de Castro Alves;Unmesh Deshmukh;Anand Srinivasan

  • Deleting a continuous query from a data stream management system continuing to operate on other queries

    Namit Jain;Anand Srinivasan;Shailendra Kumar Mishra

  • Log visualization tool for a data stream processing server

    Hoyong Park;Rakesh Komuravelli;Namit Jain;Anand Srinivasan

  • Extensible indexing framework using data cartridges

    Alexandre de Castro Alves;Unmesh Deshmukh;Hoyong Park;Shailendra Mishra

Frequent Co-Authors

Shailendra Mishra
Shailendra Mishra Business International Corporation
Namit Jain
Namit Jain Business International Corporation

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