What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Operating system
- The Internet
Shonali Krishnaswamy mainly focuses on Data stream mining, Data mining, Data stream, World Wide Web and Data science.
In most of his Data stream mining studies, his work intersects topics such as Wireless sensor network.
His work deals with themes such as Software, Scheduling and Cluster analysis, which intersect with Data mining.
His Data stream research includes elements of Process, Data warehouse, Knowledge extraction and Adaptation.
His research integrates issues of Service delivery framework, Service provider, Mobile QoS and Service level objective in his study of World Wide Web.
The Data science study which covers Field that intersects with Wireless, Process, Wireless network and Mobile device.
His most cited work include:
- Mining data streams: a review (804 citations)
- Deep convolutional neural networks on multichannel time series for human activity recognition (497 citations)
- Rank-GeoFM: A Ranking based Geographical Factorization Method for Point of Interest Recommendation (217 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Data mining, Data stream mining, World Wide Web, Mobile device and Mobile computing.
Shonali Krishnaswamy has researched Data mining in several fields, including Application service provider and Machine learning, Activity recognition, Artificial intelligence.
His Data stream mining research incorporates themes from Database, Cluster analysis, Adaptation, Data stream and Data science.
His studies deal with areas such as Ubiquitous computing and Software as well as Adaptation.
His World Wide Web research is multidisciplinary, incorporating elements of Service delivery framework, Service provider and Mobile QoS.
His work investigates the relationship between Mobile computing and topics such as Mobile search that intersect with problems in Mobile Web.
He most often published in these fields:
- Data mining (30.32%)
- Data stream mining (22.17%)
- World Wide Web (21.27%)
What were the highlights of his more recent work (between 2013-2018)?
- Data mining (30.32%)
- Artificial intelligence (12.67%)
- Machine learning (10.41%)
In recent papers he was focusing on the following fields of study:
Shonali Krishnaswamy mainly investigates Data mining, Artificial intelligence, Machine learning, Activity recognition and Data stream mining.
His study in Data mining focuses on Profiling in particular.
The concepts of his Activity recognition study are interwoven with issues in Scalability, Discriminative model and Convolutional neural network.
His Data stream mining research includes elements of Data science and Adaptation.
His work deals with themes such as Transfer of learning, Field and Adaptive learning, which intersect with Data science.
His Adaptation study combines topics from a wide range of disciplines, such as Ubiquitous computing, Data stream and Active learning.
Between 2013 and 2018, his most popular works were:
- Deep convolutional neural networks on multichannel time series for human activity recognition (497 citations)
- Rank-GeoFM: A Ranking based Geographical Factorization Method for Point of Interest Recommendation (217 citations)
- An overview of state-of-the-art partial discharge analysis techniques for condition monitoring (101 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- The Internet
Shonali Krishnaswamy mostly deals with Activity recognition, Data stream mining, Adaptation, Ubiquitous computing and Machine learning.
Shonali Krishnaswamy has included themes like Mobile broadband, Mobile computing, Mobile search and Big data in his Activity recognition study.
His Data stream mining research is multidisciplinary, incorporating perspectives in Key and Data science.
The various areas that he examines in his Adaptation study include Data stream and Active learning.
His Data stream study frequently draws connections between related disciplines such as Data mining.
As part of one scientific family, Shonali Krishnaswamy deals mainly with the area of Machine learning, narrowing it down to issues related to the Artificial intelligence, and often Collaborative filtering.
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