2013 - ACM Fellow For technical and literary contributions over a broad range of data management topics.
His scientific interests lie mostly in Algorithm, Data structure, Distributed computing, Scheduling and Set. Matching is the focus of his Algorithm research. He interconnects Theoretical computer science, Data stream mining, Data mining, Sliding window protocol and Concurrency in the investigation of issues within Data structure.
His Distributed computing research is multidisciplinary, relying on both Optimistic replication, Schedule, Reliability and Parallel computing. He combines subjects such as Computational complexity theory and Real-time computing with his study of Scheduling. Dennis Shasha has included themes like Protein function prediction, Human Phenotype Ontology, Function, Artificial intelligence and Machine learning in his Set study.
His main research concerns Data mining, Algorithm, Artificial intelligence, Theoretical computer science and Database. His Algorithm study frequently draws connections between adjacent fields such as Data structure. The Artificial intelligence study combines topics in areas such as Machine learning and Pattern recognition.
His Theoretical computer science research includes elements of Subgraph isomorphism problem and Graph.
Dennis Shasha spends much of his time researching Artificial intelligence, Set, Machine learning, Theoretical computer science and Algorithm. The study incorporates disciplines such as Quality and Pattern recognition in addition to Artificial intelligence. His work deals with themes such as Annotation, Spatial analysis and Matching, which intersect with Set.
His Theoretical computer science study incorporates themes from Concurrent data structure, Data structure, Motif and Graph. His Data structure study integrates concerns from other disciplines, such as Linearizability and Separation logic. His Algorithm research incorporates themes from Python, Software and Sensor fusion.
His primary areas of study are Reproducibility, Theoretical computer science, Machine learning, Artificial intelligence and Data mining. His biological study spans a wide range of topics, including Range, Motif, Data structure and Graph. His studies deal with areas such as Matching and Heuristics as well as Graph.
Dennis Shasha has included themes like Annotation, Set, Source code, Debugging and Root cause in his Machine learning study. His Artificial intelligence study combines topics from a wide range of disciplines, such as Pipeline and State. His study in Data mining is interdisciplinary in nature, drawing from both FASTQ format and Base calling.
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.
The dangers of replication and a solution
Jim Gray;Pat Helland;Patrick O'Neil;Dennis Shasha.
international conference on management of data (1996)
Simple fast algorithms for the editing distance between trees and related problems
K. Zhang;D. Shasha.
SIAM Journal on Computing (1989)
A gene expression map of the Arabidopsis root.
Kenneth Birnbaum;Dennis E. Shasha;Jean Y. Wang;Jee W. Jung.
StatStream: statistical monitoring of thousands of data streams in real time
Yunyue Zhu;Dennis Shasha.
very large data bases (2002)
2Q: A Low Overhead High Performance Buffer Management Replacement Algorithm
Theodore Johnson;Dennis Shasha.
very large data bases (1994)
Filtering algorithms and implementation for very fast publish/subscribe systems
Françoise Fabret;H. Arno Jacobsen;François Llirbat;Joăo Pereira.
international conference on management of data (2001)
Algorithmics and applications of tree and graph searching
Dennis Shasha;Jason T. L. Wang;Rosalba Giugno.
symposium on principles of database systems (2002)
Secure untrusted data repository (SUNDR)
Jinyuan Li;Maxwell Krohn;David Mazières;Dennis Shasha.
operating systems design and implementation (2004)
On the competitiveness of on-line real-time task scheduling
S. Baruah;G. Koren;D. Mao;B. Mishra.
Real-time Systems (1992)
Declarative Data Cleaning: Language, Model, and Algorithms
Helena Galhardas;Daniela Florescu;Dennis Shasha;Eric Simon.
very large data bases (2001)
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