What is she best known for?
The fields of study she is best known for:
- Computer network
- The Internet
- Artificial intelligence
Her primary areas of investigation include Computer network, Mobile IP, Quality of service, The Internet and Real-time computing.
Aruna Seneviratne has included themes like File sharing, Scalability and Distributed computing in her Computer network study.
Her study looks at the intersection of Mobile IP and topics like Mobility model with Radio access network.
Aruna Seneviratne has researched Quality of service in several fields, including Wireless network and Smart city.
The study incorporates disciplines such as Private information retrieval and Mobile telephony in addition to The Internet.
Her Mobile computing study incorporates themes from Mobile search and Public land mobile network.
Her most cited work include:
- S-MIP: a seamless handoff architecture for mobile IP (243 citations)
- A Survey of Wearable Devices and Challenges (189 citations)
- Histological analysis of human meniscal allografts. A preliminary report. (184 citations)
What are the main themes of her work throughout her whole career to date?
Aruna Seneviratne mainly focuses on Computer network, Mobile computing, Distributed computing, The Internet and Mobile device.
Her Computer network study combines topics in areas such as Wireless network and Mobile telephony.
The concepts of her Mobile computing study are interwoven with issues in Mobility model, Mobile search and Public land mobile network.
Her Distributed computing research is multidisciplinary, incorporating elements of Overlay network and Scalability.
Her research in Mobile device intersects with topics in Computer security, Information privacy and Access control.
Her Quality of service research includes elements of End-to-end principle, Multimedia and Mobile QoS.
She most often published in these fields:
- Computer network (50.00%)
- Mobile computing (18.04%)
- Distributed computing (15.82%)
What were the highlights of her more recent work (between 2017-2021)?
- Computer security (12.97%)
- Computer network (50.00%)
- Mobile device (14.24%)
In recent papers she was focusing on the following fields of study:
Her primary scientific interests are in Computer security, Computer network, Mobile device, Wearable computer and Information privacy.
Her work carried out in the field of Computer security brings together such families of science as Edge computing, Transaction processing and Service.
Many of her studies involve connections with topics such as Upload and Computer network.
The various areas that Aruna Seneviratne examines in her Mobile device study include Mixed reality, Augmented reality, Mobile edge computing, Access control and Reinforcement learning.
Her work deals with themes such as User information, Virtualization, Artificial intelligence and Computer vision, which intersect with Wearable computer.
Her studies in Information privacy integrate themes in fields like Scalability, External Data Representation and Network security.
Between 2017 and 2021, her most popular works were:
- A Survey of COVID-19 Contact Tracing Apps (115 citations)
- Blockchain for Secure EHRs Sharing of Mobile Cloud Based E-Health Systems (70 citations)
- HARKE: Human Activity Recognition from Kinetic Energy Harvesting Data in Wearable Devices (61 citations)
In her most recent research, the most cited papers focused on:
- Computer network
- The Internet
- Artificial intelligence
Aruna Seneviratne focuses on Wearable computer, Mobile device, Wearable technology, Data science and Blockchain.
Smartwatch and Ubiquitous computing is closely connected to Artificial intelligence in her research, which is encompassed under the umbrella topic of Wearable computer.
She combines subjects such as Mixed reality, Augmented reality, Distributed computing, Access control and Reinforcement learning with her study of Mobile device.
Her Wearable technology study combines topics from a wide range of disciplines, such as Risk analysis, Activity recognition and Computer vision.
Her Blockchain research includes themes of Unstructured Supplementary Service Data, Information privacy, Network security and Smart city.
Her Deep learning research incorporates elements of Recurrent neural network, Mel-frequency cepstrum, Computer network, Authentication and Hidden Markov model.
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