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
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 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.
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.
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.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Adding new continuous queries to a data stream management system operating on existing queries
Namit Jain;Anand Srinivasan;Shailendra Kumar Mishra.
(2007)
Support for user defined functions in a data stream management system
Anand Srinivasan;Namit Jain;Shailendra Kumar Mishra.
(2007)
Standardized database connectivity support for an event processing server
Mohit Thatte;Sandeep Bishnoi;Namit Jain;Anand Srinivasan.
(2009)
Framework for dynamically generating tuple and page classes
Hoyong Park;Namit Jain;Anand Srinivasan;Shailendra Mishra.
(2009)
Dynamically sharing a subtree of operators in a data stream management system operating on existing queries
Namit Jain;Anand Srinivasan;Shailendra Kumar Mishra.
(2007)
Variable duration non-event pattern matching
Unmesh Anil Deshmukh;Anand Srinivasan.
(2013)
Method to create a partition-by time/tuple-based window in an event processing service
Hoyong Park;Namit Jain;Anand Srinivasan;Shailendra Mishra.
(2007)
Handling Silent Relations In A Data Stream Management System
Namit Jain;Anand Srinivasan;Shailendra Kumar Mishra.
(2007)
Support for sharing computation between aggregations in a data stream management system
Anand Srinivasan;Namit Jain;Shailendra Kumar Mishra.
(2007)
Support for user defined aggregations in a data stream management system
Anand Srinivasan;Namit Jain;Shailendra Kumar Mishra.
(2007)
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