What is he best known for?
The fields of study he is best known for:
- Computer network
- The Internet
- Operating system
His primary scientific interests are in Distributed computing, Computer security, Computer network, Artificial intelligence and Machine learning.
In general Distributed computing, his work in Fault tolerance is often linked to Locality linking many areas of study.
His work carried out in the field of Computer security brings together such families of science as Information technology, Cloud computing and Taxonomy.
His study looks at the relationship between Information technology and topics such as Community cloud, which overlap with The Internet.
His work deals with themes such as Data as a service, Scalability, Overlay network and Throughput, which intersect with Computer network.
His Artificial intelligence research includes themes of Data mining and Detector.
His most cited work include:
- A view of cloud computing (7172 citations)
- Above the Clouds: A Berkeley View of Cloud Computing (5141 citations)
- Tapestry: An Infrastructure for Fault-tolerant Wide-area Location and Routing (2190 citations)
What are the main themes of his work throughout his whole career to date?
Anthony D. Joseph mainly investigates Computer network, Artificial intelligence, Distributed computing, Machine learning and Computer security.
His Computer network study integrates concerns from other disciplines, such as Wireless, Wireless network, Throughput, Scalability and The Internet.
His Artificial intelligence research is multidisciplinary, incorporating elements of Data mining and Pattern recognition.
His biological study spans a wide range of topics, including Anomaly and Denial-of-service attack.
The various areas that he examines in his Distributed computing study include Overlay network and Cloud computing.
His research on Computer security often connects related topics like Inductive transfer.
He most often published in these fields:
- Computer network (16.67%)
- Artificial intelligence (15.69%)
- Distributed computing (12.75%)
What were the highlights of his more recent work (between 2014-2021)?
- Artificial intelligence (15.69%)
- Data science (7.35%)
- Machine learning (11.27%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Data science, Machine learning, Data mining and Cloud computing.
In the field of Artificial intelligence, his study on False positive rate, Adversarial machine learning and Classifier overlaps with subjects such as Multi-task learning.
Anthony D. Joseph combines subjects such as Open research, Scalability, Data management and Big data with his study of Data science.
His Scalability study combines topics in areas such as Visualization and Petabyte.
His work on Active learning as part of general Machine learning study is frequently linked to Binary number, Model building and Weighting, therefore connecting diverse disciplines of science.
Anthony D. Joseph undertakes interdisciplinary study in the fields of Cloud computing and Acceleration through his works.
Between 2014 and 2021, his most popular works were:
- Toil enables reproducible, open source, big biomedical data analyses (261 citations)
- Adversarial Machine Learning (172 citations)
- A Berkeley View of Systems Challenges for AI (108 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- The Internet
- Operating system
His main research concerns Artificial intelligence, Machine learning, Data science, Database and Workflow.
His research in Artificial intelligence intersects with topics in Adversary model and Pattern recognition.
His study on Computational learning theory, Online machine learning and Instance-based learning is often connected to Weighting as part of broader study in Machine learning.
The Data science study combines topics in areas such as Data acquisition, Scalability, Open research and Ambiguity.
The study incorporates disciplines such as Python, Pipeline, Analytics and Big data in addition to Scalability.
His Database study incorporates themes from Biomedical data, Cloud computing, Data mining and Open source.
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