2026 Tobias Friedrich: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	47	6530	6341	308	298	332	8306

Overview

Tobias Friedrich is affiliated with the Hasso Plattner Institute in Germany and specializes primarily in Earth and Planetary Sciences. Their research spans a range of subfields including Oceanography, Atmospheric Science, Ecology, Global and Planetary Change, and Computer Vision and Pattern Recognition. The scientific topics explored in their publications include Geology and Paleoclimatology Research, Marine and Coastal Ecosystems, Oceanographic and Atmospheric Processes, Pleistocene-Era Hominins and Archaeology, Geological Formations and Processes, Methane Hydrates and Related Phenomena, and Isotope Analysis in Ecology.

They have published extensively, with a notable presence in several research venues. Frequent publication sites include the Publishing Network for Geoscientific and Environmental Data (PANGAEA) under the Alfred Wegener Institute for Polar and Marine Research, the Journal of Geophysical Research Oceans, arXiv hosted by Cornell University, Nature Communications, and Nature Geoscience.

Recent papers authored or co-authored by Tobias Friedrich are as follows:

Stochastic models support rapid peopling of Late Pleistocene Sahul, 2021, Nature Communications
Drivers of river reactivation in North Africa during the last glacial cycle, 2021, Nature Geoscience
Timing and magnitude of Southern Ocean sea ice/carbon cycle feedbacks, 2020, Proceedings of the National Academy of Sciences
Enhanced Mid-depth Southward Transport in the Northeast Atlantic at the Last Glacial Maximum Despite a Weaker AMOC, 2020, Paleoceanography and Paleoclimatology
Strong Southern African Monsoon and weak Mozambique Channel throughflow during Heinrich events: Implication for Agulhas leakage, 2021, Earth and Planetary Science Letters

Tobias Friedrich frequently collaborates with several researchers, including Syee Weldeab, Ralph R Schneider, Nils Andersen, Dieter Garbe-Schönberg, and Brian Powell. Each of these collaborators has appeared repeatedly in their co-authorship records.

Best Publications

Carbon dioxide and climate impulse response functions for the computation of greenhouse gas metrics:a multi-model analysis

Fortunat Joos;Fortunat Joos;Raphael Roth;Raphael Roth;J. S. Fuglestvedt;G. P. Peters

859
Citations
Why rumors spread so quickly in social networks

Benjamin Doerr;Mahmoud Fouz;Tobias Friedrich

477
Citations
Approximating covering problems by randomized search heuristics using multi-objective models*

Tobias Friedrich;Jun He;Nils Hebbinghaus;Frank Neumann

180
Citations
Escaping Local Optima Using Crossover With Emergent Diversity

Duc-Cuong Dang;Tobias Friedrich;Timo Kotzing;Martin S. Krejca

179
Citations
Social Networks Spread Rumors in Sublogarithmic Time

Benjamin Doerr;Mahmoud Fouz;Tobias Friedrich

168
Citations
Social networks spread rumors in sublogarithmic time

Benjamin Doerr;Mahmoud Fouz;Tobias Friedrich

166
Citations
Approximating the Least Hypervolume Contributor: NP-Hard in General, But Fast in Practice

Karl Bringmann;Tobias Friedrich

157
Citations
Do additional objectives make a problem harder

Dimo Brockhoff;Tobias Friedrich;Nils Hebbinghaus;Christian Klein

156
Citations
Hindcasting the continuum of Dansgaard–Oeschger variability: mechanisms, patterns and timing

L. Menviel;A. Timmermann;T. Friedrich;M. H. England

152
Citations
On the Effects of Adding Objectives to Plateau Functions

D. Brockhoff;T. Friedrich;N. Hebbinghaus;C. Klein

151
Citations
Proceedings of the Genetic and Evolutionary Computation Conference 2016

Tobias Friedrich;Frank Neumann;Andrew M. Sutton

146
Citations
Analysis of diversity-preserving mechanisms for global exploration*

Tobias Friedrich;Pietro S. Oliveto;Dirk Sudholt;Carsten Witt

131
Citations
Analyzing Hypervolume Indicator Based Algorithms

Dimo Brockhoff;Tobias Friedrich;Frank Neumann

129
Citations
An efficient algorithm for computing hypervolume contributions

Karl Bringmann;Tobias Friedrich

112
Citations
Maximizing submodular functions under matroid constraints by evolutionary algorithms

Tobias Friedrich;Frank Neumann

112
Citations
Neural network-based estimates of North Atlantic surface pCO2 from satellite data: A methodological study

Tobias Friedrich;Andreas Oschlies

110
Citations
Approximating the volume of unions and intersections of high-dimensional geometric objects

Karl Bringmann;Tobias Friedrich

109
Citations
Predicting the energy output of wind farms based on weather data: Important variables and their correlation

Ekaterina Vladislavleva;Tobias Friedrich;Frank Neumann;Markus Wagner

108
Citations
Approximating the least hypervolume contributor: NP-hard in general, but fast in practice

Karl Bringmann;Tobias Friedrich

107
Citations
Approximation-guided evolutionary multi-objective optimization

Karl Bringmann;Tobias Friedrich;Frank Neumann;Markus Wagner

103
Citations
Quasirandom rumor spreading

Benjamin Doerr;Tobias Friedrich;Thomas Sauerwald

102
Citations
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion

Tobias Friedrich;Frank Neumann;Andrew M. Sutton

83
Citations
Neural-network based estimates of North Atlantic surface pCO2 from satellite data - a methodological study

Tobias Friedrich

0
Citations

Frequent Co-Authors

Axel Timmermann Pusan National University

Frank Neumann University of Adelaide

Benjamin Doerr École Polytechnique

Markus Wagner Monash University

Laurie Menviel University of New South Wales

Adele Bertini University of Florence

Leonardo Sagnotti National Institute of Geophysics and Volcanology

Odile Peyron University of Montpellier

Hendrik Vogel University of Bern

Nathalie Combourieu-Nebout French National Museum of Natural History

External Links

Personal website of Tobias Friedrich Google Scholar page

If you think any of the details on this page are incorrect, let us know.

Related Online Degrees & Career Pathways

If you’re interested in Computer Science, there are several related online degrees and career pathways to consider. Fields like mechanical engineering, physics, data science, and electrical engineering closely align with computer science and offer unique perspectives and job prospects.

Those seeking a broader technical foundation might explore the cheapest online mechanical engineering degree programs, which blend engineering principles with computer modeling and analysis skills. For a science-focused path, a bachelor of science in physics online offers a strong theoretical background that’s valuable in research, data analysis, and emerging tech sectors.

Data-driven careers continue to surge in demand. Many students transition from computer science into high-growth data science programs to specialize in analytics, machine learning, and AI. Similarly, robust online options exist for computing and electronics through the online electrical engineering degree ranking—an ideal choice for those focused on hardware, communications, or systems design.

Exploring these online degree alternatives can open up interdisciplinary career opportunities, expand your technical expertise, and increase your appeal in a competitive job market.