What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- The Internet
- Operating system
His main research concerns Computer security, World Wide Web, The Internet, Database and Access control.
His biological study spans a wide range of topics, including Server, Internet privacy and Data management.
His research in The Internet intersects with topics in Role-based access control, Discretionary access control, Physical access and Network Access Control.
The various areas that he examines in his Database study include Presentation, Publication, Outsourcing, Encryption and Service provider.
His study in Access control is interdisciplinary in nature, drawing from both Metadata, Authorization and Service.
His studies in Anonymity integrate themes in fields like Polling, Resource and Peer-to-peer.
His most cited work include:
- Process Mining Manifesto (684 citations)
- A reputation-based approach for choosing reliable resources in peer-to-peer networks (603 citations)
- Augmented reality technologies, systems and applications (544 citations)
What are the main themes of his work throughout his whole career to date?
Ernesto Damiani mainly focuses on Computer security, World Wide Web, Cloud computing, Artificial intelligence and Software engineering.
Ernesto Damiani interconnects Service provider, Cloud computing security and Internet privacy in the investigation of issues within Computer security.
His works in Metadata, Web service, XML and Semantic Web are all subjects of inquiry into World Wide Web.
XML is often connected to Information retrieval in his work.
His studies deal with areas such as Machine learning, Computer vision and Pattern recognition as well as Artificial intelligence.
His Database research extends to the thematically linked field of Access control.
He most often published in these fields:
- Computer security (21.60%)
- World Wide Web (12.52%)
- Cloud computing (9.63%)
What were the highlights of his more recent work (between 2016-2021)?
- Computer security (21.60%)
- Artificial intelligence (9.35%)
- Big data (5.36%)
In recent papers he was focusing on the following fields of study:
Computer security, Artificial intelligence, Big data, Cloud computing and Data science are his primary areas of study.
His Computer security research focuses on Information security in particular.
His Artificial intelligence study incorporates themes from Machine learning, Computer vision and Pattern recognition.
His Big data study combines topics from a wide range of disciplines, such as Recommender system, Service and Internet privacy.
His Cloud computing research is multidisciplinary, incorporating perspectives in Software engineering, Adaptation and Service.
In his study, which falls under the umbrella issue of Data science, Data management and Information privacy is strongly linked to Data modeling.
Between 2016 and 2021, his most popular works were:
- Big Data and Data Analytics Research: From Metaphors to Value Space for Collective Wisdom in Human Decision Making and Smart Machines (104 citations)
- Policy making for smart cities: innovation and social inclusive economic growth for sustainability (66 citations)
- A Model-Driven Methodology for Big Data Analytics-as-a-Service (26 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- The Internet
His primary areas of investigation include Big data, Cloud computing, Computer security, Data science and Data mining.
His Big data study integrates concerns from other disciplines, such as Privacy Impact Assessment, Service, Process and Internet privacy.
His Cloud computing research includes themes of Software as a service, Service, Adaptation, Certificate and Provisioning.
His Computer security research integrates issues from Computation, Online auction and Cloud computing security.
His study on Analytics is often connected to Reputation management as part of broader study in Data science.
In his work, Process mining, Statistical classification, False alarm, Interpretation and Series is strongly intertwined with Event, which is a subfield of Data mining.
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