Eugenio Angriman

About Eugenio Angriman

Eugenio Angriman, With an exceptional h-index of 8 and a recent h-index of 8 (since 2020), a distinguished researcher at Humboldt-Universität zu Berlin, specializes in the field of Algorithms, Network Analysis, Centrality, Parallel Algorithms.

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

Algorithms for large-scale network analysis and the NetworKit toolkit

Computing top-k closeness centrality in fully dynamic graphs

A Batch-dynamic Suitor Algorithm for Approximating Maximum Weighted Matching

Interactive Visualization of Protein RINs using NetworKit in the Cloud

Scalable Algorithms for the Analysis of Massive Networks

New approximation algorithms for forest closeness centrality–for individual vertices and vertex groups

Group-Harmonic and Group-Closeness Maximization–Approximation and Engineering∗

Approximation of the diagonal of a laplacian's pseudoinverse for complex network analysis

Eugenio Angriman Information

University

Position

Ph.D. Student

Citations(all)

138

Citations(since 2020)

135

Cited By

40

hIndex(all)

8

hIndex(since 2020)

8

i10Index(all)

7

i10Index(since 2020)

7

Email

University Profile Page

Google Scholar

Eugenio Angriman Skills & Research Interests

Algorithms

Network Analysis

Centrality

Parallel Algorithms

Top articles of Eugenio Angriman

Algorithms for large-scale network analysis and the NetworKit toolkit

2023/1/18

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

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

Scalable Algorithms for the Analysis of Massive Networks

2021

Eugenio Angriman
Eugenio Angriman

H-Index: 4

New approximation algorithms for forest closeness centrality–for individual vertices and vertex groups

2021

Eugenio Angriman
Eugenio Angriman

H-Index: 4

Henning Meyerhenke
Henning Meyerhenke

H-Index: 23

Group-Harmonic and Group-Closeness Maximization–Approximation and Engineering∗

2021

Eugenio Angriman
Eugenio Angriman

H-Index: 4

Henning Meyerhenke
Henning Meyerhenke

H-Index: 23

Approximation of the diagonal of a laplacian's pseudoinverse for complex network analysis

2020/6/24

Eugenio Angriman
Eugenio Angriman

H-Index: 4

Henning Meyerhenke
Henning Meyerhenke

H-Index: 23

Scaling up network centrality computations–A brief overview

2020/5/27

Eugenio Angriman
Eugenio Angriman

H-Index: 4

Henning Meyerhenke
Henning Meyerhenke

H-Index: 23

Group centrality maximization for large-scale graphs

2020

See List of Professors in Eugenio Angriman University(Humboldt-Universität zu Berlin)