What is he best known for?
The fields of study he is best known for:
- Operating system
- Computer network
- Database
His scientific interests lie mostly in Computer hardware, Dispersed storage, Computer network, Communications system and Coding.
By researching both Computer hardware and Communication unit, he produces research that crosses academic boundaries.
Among his Dispersed storage studies, you can observe a synthesis of other disciplines of science such as Data segment, Data mining, Database, RAID processing unit and Disk array controller.
His Data segment study combines topics from a wide range of disciplines, such as Encoding and Arithmetic.
The various areas that Timothy W. Markison examines in his Computer network study include Transmitter and Reading.
His biological study spans a wide range of topics, including Identification, Electronic engineering, Communication channel and Code.
His most cited work include:
- Detection of unauthorized use of software applications in processing devices (134 citations)
- Method of configuring a communication unit using a wireless portable configuration device (115 citations)
- Method and apparatus for allocating carrier channels (100 citations)
What are the main themes of his work throughout his whole career to date?
Timothy W. Markison mostly deals with Dispersed storage, Computer hardware, Computer network, Real-time computing and Coding.
Dispersed storage is intertwined with Threshold number, Encoding, Data segment, Decoding methods and Data mining in his research.
His Computer data storage, Semiconductor memory and Registered memory study in the realm of Computer hardware connects with subjects such as Data objects.
His Computer network study combines topics in areas such as Wireless, Wireless communication systems, Controller and Embedded system.
The study of Real-time computing is intertwined with the study of Data stream in a number of ways.
In his works, Timothy W. Markison performs multidisciplinary study on Coding and Parameter.
He most often published in these fields:
- Dispersed storage (65.41%)
- Computer hardware (39.46%)
- Computer network (22.16%)
What were the highlights of his more recent work (between 2014-2021)?
- Dispersed storage (65.41%)
- Computer hardware (39.46%)
- Encoding (17.30%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Dispersed storage, Computer hardware, Encoding, Data objects and Computer network.
His Dispersed storage research spans across into subjects like Threshold number, Real-time computing, Task, Computer data storage and Algorithm.
His Real-time computing research incorporates elements of Redundancy and Schedule.
His studies in Computer hardware integrate themes in fields like Data segment, Interface, Data mining and Redundancy.
His Encoding research includes elements of Data type and Search engine indexing.
His work in Computer network addresses issues such as Database, which are connected to fields such as Filter.
Between 2014 and 2021, his most popular works were:
- Method and apparatus for nested dispersed storage (48 citations)
- Time based dispersed storage access (40 citations)
- Efficient storage of encrypted data in a dispersed storage network (26 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Computer network
- Database
Timothy W. Markison mainly focuses on Dispersed storage, Computer hardware, Encoding, Computer network and Data objects.
Timothy W. Markison performs integrative study on Dispersed storage and Data slice.
His Computer hardware research integrates issues from Filesystem-level encryption, Data mining and Distributed data store.
His Data mining research is multidisciplinary, relying on both Encryption, On-the-fly encryption and Computer data storage.
The concepts of his Encoding study are interwoven with issues in Parallel computing, Search engine indexing and Arithmetic.
His Computer network study which covers Database that intersects with User device.
This overview was generated by a machine learning system which analysed the scientist’s
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