What is he best known for?
The fields of study he is best known for:
- Operating system
- Programming language
- Database
His main research concerns Distributed computing, Data mining, Parallel computing, Application software and Virtual microscope.
His biological study spans a wide range of topics, including Common Component Architecture and Software framework.
His Data mining study combines topics in areas such as Parallel database, Raw data, Task and Implementation.
His study in the field of Distributed memory is also linked to topics like Runtime verification.
His Application software research is multidisciplinary, incorporating elements of Scheduling, CHAOS and Distributed data structures.
His Software system research is multidisciplinary, relying on both Workstation and Computer hardware.
His most cited work include:
- Distributed processing of very large datasets with DataCutter (165 citations)
- DataCutter: Middleware for Filtering Very Large Scientific Datasets on Archival Storage Systems. (162 citations)
- Programmable interconnection chip for computer system functional modules (139 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Distributed computing, Parallel computing, Grid computing, Data mining and Scalability.
His Distributed computing research includes elements of Scheduling, Computer network and Query optimization.
His research in Parallel computing intersects with topics in Compiler, Runtime library and Set.
His studies deal with areas such as Search engine indexing and Database as well as Data mining.
The various areas that Alan Sussman examines in his Scalability study include Client–server model and The Internet.
His studies deal with areas such as Physical model, Software and Theoretical computer science as well as Distributed Computing Environment.
He most often published in these fields:
- Distributed computing (39.05%)
- Parallel computing (20.12%)
- Grid computing (14.20%)
What were the highlights of his more recent work (between 2011-2019)?
- Distributed computing (39.05%)
- Load balancing (10.06%)
- Software engineering (5.33%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Distributed computing, Load balancing, Software engineering, Multi-core processor and Component-based software engineering.
His Peer-to-peer study in the realm of Distributed computing connects with subjects such as Grid computing.
His biological study spans a wide range of topics, including Scalability and Earliest deadline first scheduling, Rate-monotonic scheduling, Scheduling, Dynamic priority scheduling.
His Software engineering research is multidisciplinary, incorporating elements of White-box testing, Software reliability testing, Test strategy, Test Management Approach and Regression testing.
His Multi-core processor research integrates issues from Concurrency, Computational thinking, Java, Event and Data structure.
Alan Sussman combines subjects such as Data ingestion and Data mining with his study of Leverage.
Between 2011 and 2019, his most popular works were:
- Twenty Years of Digital Pathology: An Overview of the Road Travelled, What is on the Horizon, and the Emergence of Vendor-Neutral Archives. (46 citations)
- Topics in Parallel and Distributed Computing: Introducing Concurrency in Undergraduate Courses (15 citations)
- Literacy for all in parallel and distributed computing: guidelines for an undergraduate core curriculum (10 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Programming language
- Database
Software engineering, System integration testing, Speedup, Data mining and Range query are his primary areas of study.
His Software engineering research includes themes of White-box testing, Software reliability testing, Test strategy, Test Management Approach and Regression testing.
His study looks at the relationship between System integration testing and topics such as Systems engineering, which overlap with Software development and Component.
His Speedup study incorporates themes from Information retrieval, Search engine indexing and Multidimensional indexing.
His Data mining study combines topics in areas such as Data ingestion and Leverage.
A majority of his Suite research is a blend of other scientific areas, such as Distributed computing and Data management.
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