What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Programming language
His primary areas of investigation include Artificial intelligence, Cryptography, Secret sharing, Theoretical computer science and Information management.
His work deals with themes such as Medical diagnosis, Computer vision and Natural language processing, which intersect with Artificial intelligence.
His research integrates issues of Computational intelligence and Interpretation in his study of Computer vision.
The concepts of his Cryptography study are interwoven with issues in Information sharing and Human–computer interaction.
His Theoretical computer science study combines topics in areas such as Secure multi-party computation, Homomorphic secret sharing, Grammar and Rule-based machine translation.
His Information management study integrates concerns from other disciplines, such as Computer security, Formal grammar and Data science.
His most cited work include:
- Knowledge discovery approach to automated cardiac SPECT diagnosis (213 citations)
- Medical Image Understanding Technology (160 citations)
- Rule-based approach to recognizing human body poses and gestures in real time (81 citations)
What are the main themes of his work throughout his whole career to date?
Marek R. Ogiela mainly focuses on Artificial intelligence, Natural language processing, Computer security, Cryptography and Computer vision.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning and Pattern recognition.
His Rule-based machine translation study in the realm of Natural language processing interacts with subjects such as Rotation formalisms in three dimensions.
His studies examine the connections between Computer security and genetics, as well as such issues in Information management, with regards to Information sharing, Data management and Personal information management.
His studies deal with areas such as Encryption, Human–computer interaction and Biometrics as well as Cryptography.
He interconnects Secure multi-party computation and Theoretical computer science in the investigation of issues within Secret sharing.
He most often published in these fields:
- Artificial intelligence (43.43%)
- Natural language processing (17.69%)
- Computer security (16.89%)
What were the highlights of his more recent work (between 2017-2021)?
- Cryptography (13.94%)
- Computer security (16.89%)
- Cryptographic protocol (9.65%)
In recent papers he was focusing on the following fields of study:
His main research concerns Cryptography, Computer security, Cryptographic protocol, CAPTCHA and Human–computer interaction.
His Cryptography research is multidisciplinary, relying on both Information management, Data management, Encryption and Personally identifiable information.
His Authentication, Blockchain, Data security and Cloud storage study in the realm of Computer security connects with subjects such as Audit.
His study looks at the relationship between Cryptographic protocol and fields such as Context, as well as how they intersect with chemical problems.
His Normalization study is concerned with Artificial intelligence in general.
His work on Lemmatisation as part of general Artificial intelligence study is frequently linked to Bigram, therefore connecting diverse disciplines of science.
Between 2017 and 2021, his most popular works were:
- Cognitive security paradigm for cloud computing applications (11 citations)
- Multiply information coding and hiding using fuzzy vault (7 citations)
- Cognitive cryptography techniques for intelligent information management (5 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Programming language
His primary areas of study are Data science, Computer security, Cryptography, Artificial intelligence and Motion capture.
His Data science research focuses on subjects like Focus, which are linked to Information management.
His work in the fields of Computer security, such as Cryptographic protocol, Homomorphic encryption and Cloud storage, intersects with other areas such as Audit.
His Cryptography research includes themes of Authentication, Encryption and Personally identifiable information.
The various areas that he examines in his Artificial intelligence study include Computer vision and Pattern recognition.
Marek R. Ogiela combines subjects such as Dynamic time warping, Repetition and Support vector machine with his study of Motion capture.
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