H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 79 Citations 24,462 267 World Ranking 462 National Ranking 275

Research.com Recognitions

Awards & Achievements

2013 - ACM Fellow For technical and literary contributions over a broad range of data management topics.

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • Artificial intelligence
  • Programming language

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 most cited work include:

  • Simple fast algorithms for the editing distance between trees and related problems (1103 citations)
  • The dangers of replication and a solution (1089 citations)
  • A gene expression map of the Arabidopsis root. (1050 citations)

What are the main themes of his work throughout his whole career to date?

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.

He most often published in these fields:

  • Data mining (13.02%)
  • Algorithm (11.63%)
  • Artificial intelligence (9.07%)

What were the highlights of his more recent work (between 2014-2021)?

  • Artificial intelligence (9.07%)
  • Set (5.58%)
  • Machine learning (4.88%)

In recent papers he was focusing on the following fields of study:

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.

Between 2014 and 2021, his most popular works were:

  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy (241 citations)
  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy (184 citations)
  • Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants (69 citations)

In his most recent research, the most cited papers focused on:

  • Operating system
  • Artificial intelligence
  • Statistics

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.

Top Publications

The dangers of replication and a solution

Jim Gray;Pat Helland;Patrick O'Neil;Dennis Shasha.
international conference on management of data (1996)

1748 Citations

Simple fast algorithms for the editing distance between trees and related problems

K. Zhang;D. Shasha.
SIAM Journal on Computing (1989)

1581 Citations

A gene expression map of the Arabidopsis root.

Kenneth Birnbaum;Dennis E. Shasha;Jean Y. Wang;Jee W. Jung.
Science (2003)

1259 Citations

StatStream: statistical monitoring of thousands of data streams in real time

Yunyue Zhu;Dennis Shasha.
very large data bases (2002)

920 Citations

2Q: A Low Overhead High Performance Buffer Management Replacement Algorithm

Theodore Johnson;Dennis Shasha.
very large data bases (1994)

872 Citations

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)

712 Citations

Algorithmics and applications of tree and graph searching

Dennis Shasha;Jason T. L. Wang;Rosalba Giugno.
symposium on principles of database systems (2002)

578 Citations

Secure untrusted data repository (SUNDR)

Jinyuan Li;Maxwell Krohn;David Mazières;Dennis Shasha.
operating systems design and implementation (2004)

551 Citations

Declarative Data Cleaning: Language, Model, and Algorithms

Helena Galhardas;Daniela Florescu;Dennis Shasha;Eric Simon.
very large data bases (2001)

499 Citations

Efficient and Correct Execution of Parallel Programs That Share Memory

Dennis Shasha;Marc Snir.
(2011)

452 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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