H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 62 Citations 20,927 135 World Ranking 1390 National Ranking 790

Research.com Recognitions

Awards & Achievements

2011 - Fellow of Alfred P. Sloan Foundation

Overview

What is he best known for?

The fields of study he is best known for:

  • Computer network
  • Operating system
  • The Internet

His primary scientific interests are in Computer network, Distributed computing, Key, Scalability and Operating system. Many of his studies involve connections with topics such as The Internet and Computer network. His Distributed computing research is multidisciplinary, relying on both Latency, Latency and Paxos.

His study in Key is interdisciplinary in nature, drawing from both Joule, Computer cluster, Replication, Parallel computing and Hash function. His Scalability study incorporates themes from Throughput, Consistency model and Server. His work deals with themes such as IP forwarding, Transmission Control Protocol, Fault detection and isolation, Key-based routing and Routing protocol, which intersect with Overlay network.

His most cited work include:

  • Resilient overlay networks (1941 citations)
  • Scaling distributed machine learning with the parameter server (846 citations)
  • c-Through: part-time optics in data centers (555 citations)

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

David G. Andersen spends much of his time researching Computer network, Distributed computing, Operating system, Scalability and The Internet. His Computer network study integrates concerns from other disciplines, such as Overlay network and Throughput. His study on Load balancing is often connected to Causal consistency as part of broader study in Distributed computing.

His Operating system study combines topics in areas such as Key and Efficient energy use. His Scalability study integrates concerns from other disciplines, such as Remote direct memory access, Ethernet and Multi-core processor. As part of one scientific family, David G. Andersen deals mainly with the area of The Internet, narrowing it down to issues related to the Computer security, and often Internet protocol suite.

He most often published in these fields:

  • Computer network (33.12%)
  • Distributed computing (25.63%)
  • Operating system (11.88%)

What were the highlights of his more recent work (between 2016-2021)?

  • Data structure (8.12%)
  • Algorithm (5.62%)
  • Artificial intelligence (5.62%)

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

The scientist’s investigation covers issues in Data structure, Algorithm, Artificial intelligence, Bloom filter and Distributed computing. David G. Andersen interconnects Tree, Entropy, Encoder and Theoretical computer science in the investigation of issues within Data structure. His Artificial intelligence research incorporates themes from Fuse, Frame and Machine learning.

David G. Andersen has included themes like Artificial neural network, Block, Memory management, Scheduling and Implementation in his Distributed computing study. He studied Implementation and Microservices that intersect with Scalability. His studies examine the connections between Scalability and genetics, as well as such issues in Replication, with regards to Computer network and Multi-core processor.

Between 2016 and 2021, his most popular works were:

  • Cicada: Dependably Fast Multi-Core In-Memory Transactions (56 citations)
  • SuRF: Practical Range Query Filtering with Fast Succinct Tries (53 citations)
  • Datacenter RPCs can be general and fast (52 citations)

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

  • Computer network
  • Operating system
  • The Internet

Distributed computing, Cloud computing, Algorithm, Scalability and Source code are his primary areas of study. His Distributed computing research integrates issues from Frame rate, Enhanced Data Rates for GSM Evolution, Aggregate, Video processing and Transfer of learning. His study in Cloud computing is interdisciplinary in nature, drawing from both Real-time computing, Backhaul, Analytics and Wide area network.

His biological study spans a wide range of topics, including Backpropagation, Image and Selection. His Scalability research includes themes of Latency, Granularity, Microservices, Preemption and Scheduling. His Source code study combines topics from a wide range of disciplines, such as Remote procedure call, Remote direct memory access, Computer network, State machine replication and Packet loss.

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

Resilient overlay networks

David Andersen;Hari Balakrishnan;Frans Kaashoek;Robert Morris.
symposium on operating systems principles (2001)

2917 Citations

Scaling distributed machine learning with the parameter server

Mu Li;David G. Andersen;Jun Woo Park;Alexander J. Smola.
operating systems design and implementation (2014)

1037 Citations

Don't settle for eventual: scalable causal consistency for wide-area storage with COPS

Wyatt Lloyd;Michael J. Freedman;Michael Kaminsky;David G. Andersen.
symposium on operating systems principles (2011)

765 Citations

c-Through: part-time optics in data centers

Guohui Wang;David G. Andersen;Michael Kaminsky;Konstantina Papagiannaki.
acm special interest group on data communication (2010)

751 Citations

FAWN: a fast array of wimpy nodes

David G. Andersen;Jason Franklin;Michael Kaminsky;Amar Phanishayee.
symposium on operating systems principles (2009)

728 Citations

Safe and effective fine-grained TCP retransmissions for datacenter communication

Vijay Vasudevan;Amar Phanishayee;Hiral Shah;Elie Krevat.
acm special interest group on data communication (2009)

508 Citations

MICA: a holistic approach to fast in-memory key-value storage

Hyeontaek Lim;Dongsu Han;David G. Andersen;Michael Kaminsky.
networked systems design and implementation (2014)

482 Citations

SILT: a memory-efficient, high-performance key-value store

Hyeontaek Lim;Bin Fan;David G. Andersen;Michael Kaminsky.
symposium on operating systems principles (2011)

478 Citations

Accountable internet protocol (aip)

David G. Andersen;Hari Balakrishnan;Nick Feamster;Teemu Koponen.
acm special interest group on data communication (2008)

440 Citations

Communication Efficient Distributed Machine Learning with the Parameter Server

Mu Li;David G Andersen;Alex J Smola;Kai Yu.
neural information processing systems (2014)

431 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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