Henning Meyerhenke

About Henning Meyerhenke

Henning Meyerhenke, With an exceptional h-index of 31 and a recent h-index of 23 (since 2020), a distinguished researcher at Humboldt-Universität zu Berlin, specializes in the field of Scalable graph algorithms, algorithmic network analysis, combinatorial scientific computing.

His recent articles reflect a diverse array of research interests and contributions to the field:

4 Open Problems 4.1 Open Problems in Benchmarking Graph Learning via Synthetic Graph Generation

5 Working Groups 5.1 Working Group on Causal Representation Learning

The global interdependence patterns of extreme-rainfall events

Scalable Graph Mining and Learning (Dagstuhl Seminar 23491)

Mapping tree‐shaped workflows on systems with different memory sizes and processor speeds

Methodology of Algorithm Engineering

Greedy optimization of resistance-based graph robustness with global and local edge insertions

More recent advances in (hyper) graph partitioning

Henning Meyerhenke Information

University

Position

Professor of Computer Science

Citations(all)

4208

Citations(since 2020)

2419

Cited By

2738

hIndex(all)

31

hIndex(since 2020)

23

i10Index(all)

62

i10Index(since 2020)

47

Email

University Profile Page

Google Scholar

Henning Meyerhenke Skills & Research Interests

Scalable graph algorithms

algorithmic network analysis

combinatorial scientific computing

Top articles of Henning Meyerhenke

4 Open Problems 4.1 Open Problems in Benchmarking Graph Learning via Synthetic Graph Generation

Scalable Graph Mining and Learning

2024/4

5 Working Groups 5.1 Working Group on Causal Representation Learning

Scalable Graph Mining and Learning

2024/4

The global interdependence patterns of extreme-rainfall events

2024/3/7

Henning Meyerhenke
Henning Meyerhenke

H-Index: 23

Scalable Graph Mining and Learning (Dagstuhl Seminar 23491)

2024

Mapping tree‐shaped workflows on systems with different memory sizes and processor speeds

Concurrency and Computation: Practice and Experience

2023/11/15

Henning Meyerhenke
Henning Meyerhenke

H-Index: 23

Anne Benoit
Anne Benoit

H-Index: 17

Methodology of Algorithm Engineering

arXiv preprint arXiv:2310.18979

2023/10/29

Greedy optimization of resistance-based graph robustness with global and local edge insertions

Social Network Analysis and Mining

2023/10/12

Robert Kooij
Robert Kooij

H-Index: 21

Henning Meyerhenke
Henning Meyerhenke

H-Index: 23

Algorithms for large-scale network analysis and the NetworKit toolkit

2023/1/18

Faster greedy optimization of resistance-based graph robustness

2022/11/10

Robert Kooij
Robert Kooij

H-Index: 21

Henning Meyerhenke
Henning Meyerhenke

H-Index: 23

Network Sparsification via Degree-and Subgraph-based Edge Sampling

2022/11/10

Henning Meyerhenke
Henning Meyerhenke

H-Index: 23

An MPI-Parallel Algorithm for Static and Dynamic Top-k Harmonic Centrality

2022/11/2

Henning Meyerhenke
Henning Meyerhenke

H-Index: 23

Fast Dynamic Updates and Dynamic SpGEMM on MPI-Distributed Graphs

2022/9/5

Henning Meyerhenke
Henning Meyerhenke

H-Index: 23

Mapping tree-shaped workflows on memory-heterogeneous architectures

2022/8/22

Henning Meyerhenke
Henning Meyerhenke

H-Index: 23

Anne Benoit
Anne Benoit

H-Index: 17

Computing top-k closeness centrality in fully dynamic graphs

2022/7/20

Eugenio Angriman
Eugenio Angriman

H-Index: 4

Henning Meyerhenke
Henning Meyerhenke

H-Index: 23

A Batch-dynamic Suitor Algorithm for Approximating Maximum Weighted Matching

ACM Journal of Experimental Algorithmics (JEA)

2022/7/7

Eugenio Angriman
Eugenio Angriman

H-Index: 4

Henning Meyerhenke
Henning Meyerhenke

H-Index: 23

Scalable Katz Ranking Computation in Large Static and Dynamic Graphs

ACM Journal of Experimental Algorithmics (JEA)

2022/7/7

Oded Green
Oded Green

H-Index: 15

Henning Meyerhenke
Henning Meyerhenke

H-Index: 23

Interactive Visualization of Protein RINs using NetworKit in the Cloud

2022/5/30

Eugenio Angriman
Eugenio Angriman

H-Index: 4

Henning Meyerhenke
Henning Meyerhenke

H-Index: 23

Tarema: Adaptive resource allocation for scalable scientific workflows in heterogeneous clusters

2021/12/15

See List of Professors in Henning Meyerhenke University(Humboldt-Universität zu Berlin)

Co-Authors

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