What is he best known for?
The fields of study he is best known for:
- Operating system
- Database
- Programming language
His primary scientific interests are in Wireless sensor network, Database, Distributed computing, Real-time computing and Query optimization.
His Wireless sensor network research incorporates themes from Data acquisition and Key distribution in wireless sensor networks, Wireless network.
Database is frequently linked to Data science in his study.
His Distributed computing research focuses on subjects like Set, which are linked to Adaptive optimization and Response time.
His Real-time computing research is multidisciplinary, incorporating perspectives in Simulation, Software deployment, Global Positioning System and Data visualization.
His studies in Query optimization integrate themes in fields like Query language, Query expansion and Sargable.
His most cited work include:
- TAG: a Tiny AGgregation service for Ad-Hoc sensor networks (2753 citations)
- TinyDB: an acquisitional query processing system for sensor networks (1799 citations)
- TinyOS: An Operating System for Sensor Networks (1111 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Database, Wireless sensor network, Data mining, Distributed computing and Real-time computing.
His Wireless sensor network study integrates concerns from other disciplines, such as Data acquisition, Key distribution in wireless sensor networks, Data management and Query optimization.
Samuel Madden has researched Query optimization in several fields, including Query expansion and Sargable.
His Data mining research focuses on Set and how it relates to Massively parallel.
Real-time computing is closely attributed to Global Positioning System in his study.
His Computer network study combines topics in areas such as Wireless and Wireless network.
He most often published in these fields:
- Database (24.23%)
- Wireless sensor network (15.64%)
- Data mining (14.11%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (8.59%)
- Analytics (6.44%)
- Data mining (14.11%)
In recent papers he was focusing on the following fields of study:
Samuel Madden spends much of his time researching Artificial intelligence, Analytics, Data mining, Set and Information retrieval.
His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning and Pattern recognition.
The concepts of his Data mining study are interwoven with issues in Inverted index, Hash function and Global Positioning System.
Samuel Madden focuses mostly in the field of Key, narrowing it down to matters related to Snapshot and, in some cases, Distributed computing.
Samuel Madden combines topics linked to Database with his work on Bandwidth.
Particularly relevant to Replication is his body of work in Database.
Between 2018 and 2021, his most popular works were:
- SageDB: A Learned Database System (74 citations)
- Raha: A Configuration-Free Error Detection System (20 citations)
- MLSys: The New Frontier of Machine Learning Systems (15 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Database
- Programming language
His primary areas of investigation include Artificial intelligence, Set, Data mining, Process and Debugger.
His Artificial intelligence research includes elements of Machine learning, Software system, Software deployment and Natural language processing.
His study looks at the relationship between Set and fields such as Analytics, as well as how they intersect with chemical problems.
Many of his studies on Data mining apply to Contrast as well.
Samuel Madden focuses mostly in the field of Process, narrowing it down to topics relating to Object detection and, in certain cases, Component, Key, Real-time computing and Baseline.
The study incorporates disciplines such as Visualization, Workflow and Code in addition to Debugger.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
