What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Operating system
- Machine learning
His main research concerns Operations research, Artificial intelligence, Data science, Information technology and Risk analysis.
Soundar R. T. Kumara focuses mostly in the field of Operations research, narrowing it down to topics relating to Software deployment and, in certain cases, Radio-frequency identification, Business process and Operations management.
Soundar R. T. Kumara has researched Artificial intelligence in several fields, including Engineering management, Information and Communications Technology, The Internet and Cyber-physical system.
The various areas that Soundar R. T. Kumara examines in his Data science study include Emerging technologies and Network science.
His research integrates issues of Supply chain and Survivability in his study of Risk analysis.
His Supply chain research integrates issues from Network topology and Computer network.
His most cited work include:
- Near linear time algorithm to detect community structures in large-scale networks. (2161 citations)
- Cyber-physical systems in manufacturing (656 citations)
- Supply-chain networks: a complex adaptive systems perspective (388 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Artificial intelligence, Distributed computing, Operations research, Artificial neural network and Systems engineering.
His biological study spans a wide range of topics, including Machine learning and Pattern recognition.
In his work, Quality of service is strongly intertwined with Multi-agent system, which is a subfield of Distributed computing.
His work on Supply chain expands to the thematically related Operations research.
His research combines Process and Artificial neural network.
His work deals with themes such as New product development, Product design, Product engineering, Process and Engineering design process, which intersect with Systems engineering.
He most often published in these fields:
- Artificial intelligence (16.73%)
- Distributed computing (10.89%)
- Operations research (10.12%)
What were the highlights of his more recent work (between 2014-2021)?
- Artificial intelligence (16.73%)
- Machine learning (4.28%)
- Systems engineering (8.95%)
In recent papers he was focusing on the following fields of study:
Artificial intelligence, Machine learning, Systems engineering, Smart manufacturing and Algorithm are his primary areas of study.
His Artificial intelligence research includes themes of Pattern recognition, Recurrence quantification analysis, Coronavirus disease 2019 and Recurrence plot.
His study in Machine learning is interdisciplinary in nature, drawing from both Text mining, Resource, Tool wear and State.
Soundar R. T. Kumara interconnects Ontology, Risk analysis and Metamodeling in the investigation of issues within Systems engineering.
In his study, Soundar R. T. Kumara carries out multidisciplinary Algorithm and Cluster research.
He works mostly in the field of Cluster analysis, limiting it down to topics relating to Class and, in certain cases, Node.
Between 2014 and 2021, his most popular works were:
- Cyber-physical systems in manufacturing (656 citations)
- Cloud-enabled prognosis for manufacturing (200 citations)
- A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests (150 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Machine learning
His primary areas of investigation include Artificial intelligence, Machine learning, Cloud computing, Tool wear and The Internet.
The Artificial intelligence study combines topics in areas such as Block and Time series.
Soundar R. T. Kumara combines subjects such as Emerging technologies, Simulation, Network science, Manufacturing and Data science with his study of Cloud computing.
His studies in Tool wear integrate themes in fields like Online machine learning and Random forest.
His Random forest research focuses on subjects like Generalization error, which are linked to Data mining.
He interconnects Information and Communications Technology, Cyber-physical system, Computer engineering and Engineering management in the investigation of issues within The Internet.
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