What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer network
- Operating system
Wireless sensor network, Artificial intelligence, Distributed computing, Algorithm and Sensor fusion are his primary areas of study.
His Wireless sensor network research integrates issues from Node, Key distribution in wireless sensor networks, Real-time computing and Fault tolerance.
His Artificial intelligence study incorporates themes from Computer vision and Pattern recognition.
His Distributed computing study combines topics from a wide range of disciplines, such as Routing, Brooks–Iyengar algorithm, Network topology, Wide area network and Communications system.
His work deals with themes such as Word error rate, Mathematical optimization and Hit rate, which intersect with Algorithm.
His Sensor fusion research incorporates elements of Visual sensor network, Distributed services, Hybrid algorithm, Grid and Soft computing.
His most cited work include:
- Grid coverage for surveillance and target location in distributed sensor networks (842 citations)
- Distributed Bayesian algorithms for fault-tolerant event region detection in wireless sensor networks (575 citations)
- Sensor placement for grid coverage under imprecise detections (291 citations)
What are the main themes of his work throughout his whole career to date?
S. Sitharama Iyengar mostly deals with Artificial intelligence, Wireless sensor network, Computer network, Distributed computing and Algorithm.
In his research on the topic of Artificial intelligence, Terrain is strongly related with Computer vision.
S. Sitharama Iyengar interconnects Sensor node, Key distribution in wireless sensor networks, Real-time computing, Node and Sensor fusion in the investigation of issues within Wireless sensor network.
His research ties Brooks–Iyengar algorithm and Distributed computing together.
Algorithm connects with themes related to Theoretical computer science in his study.
The Dynamic Source Routing study combines topics in areas such as Link-state routing protocol, Static routing and Wireless Routing Protocol.
He most often published in these fields:
- Artificial intelligence (17.84%)
- Wireless sensor network (16.98%)
- Computer network (16.48%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (17.84%)
- Information retrieval (4.21%)
- Data science (2.85%)
In recent papers he was focusing on the following fields of study:
S. Sitharama Iyengar mainly investigates Artificial intelligence, Information retrieval, Data science, Computer security and Big data.
In his study, Identification is strongly linked to Pattern recognition, which falls under the umbrella field of Artificial intelligence.
His studies in Information retrieval integrate themes in fields like Exploit, Preference and Encyclopedia.
His Data science study integrates concerns from other disciplines, such as Work, Inclusion, Collaborative knowledge and Knowledge building.
His Computer security research includes themes of Cloud computing and Information system.
S. Sitharama Iyengar has researched Scheme in several fields, including Computer network and SCADA.
Between 2017 and 2021, his most popular works were:
- A Survey on Deep Learning: Algorithms, Techniques, and Applications (270 citations)
- Multimedia Big Data Analytics: A Survey (78 citations)
- Searching for the IoT Resources: Fundamentals, Requirements, Comprehensive Review, and Future Directions (70 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer network
- Operating system
His primary scientific interests are in Artificial intelligence, Information retrieval, Artificial neural network, Data science and Big data.
His Artificial intelligence study focuses on Feature selection in particular.
His work in Artificial neural network addresses subjects such as Deep learning, which are connected to disciplines such as Convolutional neural network and Click fraud.
His studies deal with areas such as Social network analysis, Algorithm, Unsupervised learning and Text processing as well as Convolutional neural network.
The study incorporates disciplines such as Work, Inclusion, Information technology and Knowledge building in addition to Data science.
The various areas that he examines in his Big data study include Mobile technology, Analytics and Graph.
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