D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 56 Citations 58,173 141 World Ranking 2068 National Ranking 1130

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • Programming language
  • Artificial intelligence

Matei Zaharia mainly investigates Distributed computing, Spark, Computer cluster, Scheduling and Cloud computing. His Distributed computing research is multidisciplinary, relying on both Latency, Data center, Programming paradigm and Parallel computing. His studies deal with areas such as Scalability, Partition and Computer data storage as well as Computer cluster.

The study incorporates disciplines such as Computer security, Information technology, Bioinformatics and Identification in addition to Cloud computing. His Computer security study combines topics from a wide range of disciplines, such as Software as a service, Elasticity and Server. Matei Zaharia works mostly in the field of Fault tolerance, limiting it down to topics relating to Distributed memory and, in certain cases, State, as a part of the same area of interest.

His most cited work include:

  • A view of cloud computing (7172 citations)
  • Above the Clouds: A Berkeley View of Cloud Computing (5141 citations)
  • Spark: cluster computing with working sets (3481 citations)

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

His scientific interests lie mostly in Artificial intelligence, Distributed computing, Machine learning, Spark and Cloud computing. In the field of Artificial intelligence, his study on Deep learning, Artificial neural network, Inference and Leverage overlaps with subjects such as Sample. His Distributed computing study which covers Scheduling that intersects with Optimization problem.

His work on Selection, Active learning, Proxy and Feature as part of general Machine learning research is frequently linked to Matching, bridging the gap between disciplines. His research integrates issues of Computer security, Software and Database in his study of Cloud computing. His Computer cluster research incorporates elements of Shared resource and Programming paradigm.

He most often published in these fields:

  • Artificial intelligence (24.86%)
  • Distributed computing (17.13%)
  • Machine learning (15.47%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (24.86%)
  • Machine learning (15.47%)
  • Set (6.08%)

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

His main research concerns Artificial intelligence, Machine learning, Set, Deep learning and Leverage. His Artificial intelligence research incorporates themes from Consistency, CUDA and Distributed computing. His Consistency study combines topics in areas such as Cloud computing and Data warehouse.

His Data aware study in the realm of Distributed computing connects with subjects such as Shell. His Machine learning course of study focuses on Inference and Bottleneck and Preprocessor. He combines subjects such as Optimization problem and Scheduling, Job shop scheduling with his study of Deep learning.

Between 2019 and 2021, his most popular works were:

  • ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT (64 citations)
  • Improving the Accuracy, Scalability, and Performance of Graph Neural Networks with Roc (25 citations)
  • Sparse GPU Kernels for Deep Learning (23 citations)

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

  • Operating system
  • Artificial intelligence
  • Programming language

His primary areas of investigation include Artificial intelligence, Machine learning, Artificial neural network, Deep learning and Training. Many of his research projects under Artificial intelligence are closely connected to Natural with Natural, tying the diverse disciplines of science together. His work in the fields of Machine learning, such as Active learning, overlaps with other areas such as Visual analytics.

His Artificial neural network research is multidisciplinary, incorporating perspectives in Language model, Natural language understanding, Leverage, Information retrieval and Ranking. His Deep learning research is multidisciplinary, incorporating elements of CUDA, Distributed computing and Kernel. His work deals with themes such as Field-programmable gate array, Optimization problem and Scheduling, Job shop scheduling, which intersect with CUDA.

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.

Best Publications

A view of cloud computing

Michael Armbrust;Armando Fox;Rean Griffith;Anthony D. Joseph.
Communications of The ACM (2010)

14055 Citations

Above the Clouds: A Berkeley View of Cloud Computing

Michael Armbrust;Armando Fox;Rean Griffith;Anthony D. Joseph.
Science (2009)

8882 Citations

Spark: cluster computing with working sets

Matei Zaharia;Mosharaf Chowdhury;Michael J. Franklin;Scott Shenker.
ieee international conference on cloud computing technology and science (2010)

5445 Citations

Resilient distributed datasets: a fault-tolerant abstraction for in-memory cluster computing

Matei Zaharia;Mosharaf Chowdhury;Tathagata Das;Ankur Dave.
networked systems design and implementation (2012)

4670 Citations

Improving MapReduce performance in heterogeneous environments

Matei Zaharia;Andy Konwinski;Anthony D. Joseph;Randy Katz.
operating systems design and implementation (2008)

2091 Citations

Mesos: a platform for fine-grained resource sharing in the data center

Benjamin Hindman;Andy Konwinski;Matei Zaharia;Ali Ghodsi.
networked systems design and implementation (2011)

1876 Citations

Delay scheduling: a simple technique for achieving locality and fairness in cluster scheduling

Matei Zaharia;Dhruba Borthakur;Joydeep Sen Sarma;Khaled Elmeleegy.
european conference on computer systems (2010)

1651 Citations

Apache Spark: a unified engine for big data processing

Matei Zaharia;Reynold S. Xin;Patrick Wendell;Tathagata Das.
Communications of The ACM (2016)

1334 Citations

MLlib: machine learning in apache spark

Xiangrui Meng;Joseph Bradley;Burak Yavuz;Evan Sparks.
Journal of Machine Learning Research (2016)

1282 Citations

Spark SQL: Relational Data Processing in Spark

Michael Armbrust;Reynold S. Xin;Cheng Lian;Yin Huai.
international conference on management of data (2015)

1124 Citations

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Best Scientists Citing Matei Zaharia

Rajkumar Buyya

Rajkumar Buyya

University of Melbourne

Publications: 125

Hai Jin

Hai Jin

Huazhong University of Science and Technology

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Ion Stoica

Ion Stoica

University of California, Berkeley

Publications: 89

Rajiv Ranjan

Rajiv Ranjan

Newcastle University

Publications: 71

Charles Y. Chiu

Charles Y. Chiu

University of California, San Francisco

Publications: 63

Baochun Li

Baochun Li

University of Toronto

Publications: 60

Volker Markl

Volker Markl

Technical University of Berlin

Publications: 59

Sherif Sakr

Sherif Sakr

University of Tartu

Publications: 58

Francisco Herrera

Francisco Herrera

University of Granada

Publications: 56

Albert Y. Zomaya

Albert Y. Zomaya

University of Sydney

Publications: 55

Schahram Dustdar

Schahram Dustdar

TU Wien

Publications: 52

Bingsheng He

Bingsheng He

National University of Singapore

Publications: 50

Jinjun Chen

Jinjun Chen

Swinburne University of Technology

Publications: 50

Joseph E. Gonzalez

Joseph E. Gonzalez

University of California, Berkeley

Publications: 49

Victor Chang

Victor Chang

Aston University

Publications: 47

Geoffrey C. Fox

Geoffrey C. Fox

Indiana University

Publications: 44

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