The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Daniel Delling sits on this spectrum.
This scientist: 115 publications — 13th percentile
13% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 991 publications or more.
The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Daniel Delling sits on this spectrum.
This scientist: 44 D-Index — 48th percentile
48% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 131 D-Index or more.
Daniel Delling is affiliated with Apple in the United States and has a research profile focused primarily on engineering and computer science. Their work spans a range of specialized subfields, including signal processing, automotive engineering, computer graphics and computer-aided design, computer vision and pattern recognition, and building and construction.
The research contributions of Daniel Delling are concentrated in topics such as data management and algorithms, computational geometry and mesh generation, graph theory and algorithms, traffic prediction and management techniques, transportation planning and optimization, transportation and mobility innovations, and electric vehicles and infrastructure.
Delling has published several papers in notable venues, reflecting these research interests. Key publications include:
The frequent publication venues where Delling's work appears include:
Delling regularly collaborates with a select group of coauthors. Frequent collaborators include Thomas Pajor, Renato F. Werneck, Dennis Schieferdecker, Michael Wegner, and Andrew V. Goldberg.
The combination of expertise in both algorithm development and transportation systems is reflected in the integration of research topics such as transportation planning, electric vehicle infrastructure, and graph algorithms tailored to route and traffic optimization. This interdisciplinary approach supports complex problem solving in mobility innovations and infrastructure resilience.
U. Brandes;D. Delling;M. Gaertler;R. Gorke
Robert Geisberger;Peter Sanders;Dominik Schultes;Daniel Delling
Hannah Bast;Daniel Delling;Andrew V. Goldberg;Matthias Müller-Hannemann
Daniel Delling;Peter Sanders;Dominik Schultes;Dorothea Wagner
Daniel Delling;Thomas Pajor;Renato F. Werneck
Reinhard Bauer;Daniel Delling
Ittai Abraham;Daniel Delling;Andrew V. Goldberg;Renato F. Werneck
Reinhard Bauer;Daniel Delling;Peter Sanders;Dennis Schieferdecker
Ulrik Brandes;Daniel Delling;Marco Gaertler;Robert Görke
Daniel Delling;Andrew V. Goldberg;Andreas Nowatzyk;Renato F. Werneck
Edith Cohen;Daniel Delling;Thomas Pajor;Renato F. Werneck
Ittai Abraham;Daniel Delling;Andrew V. Goldberg;Renato F. Werneck
Daniel Delling;Andrew V. Goldberg;Thomas Pajor;Renato F. Werneck
U. Brandes;D. Delling;M. Gaertler;R. Goerke
Ittai Abraham;Daniel Delling;Andrew V. Goldberg;Renato F. Werneck
Daniel Delling;Andrew V. Goldberg;Thomas Pajor;Renato F. Werneck
Daniel Delling;Dorothea Wagner
Giacomo Nannicini;Daniel Delling;Dominik Schultes;Leo Liberti
Daniel Delling;Dorothea Wagner
Daniel Delling;Andrew V. Goldberg;Ilya Razenshteyn;Renato F. Werneck
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