Steffen Lange

4.1k total citations · 2 hit papers
88 papers, 2.2k citations indexed

About

Steffen Lange is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Economics and Econometrics. According to data from OpenAlex, Steffen Lange has authored 88 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Artificial Intelligence, 26 papers in Computational Theory and Mathematics and 12 papers in Economics and Econometrics. Recurrent topics in Steffen Lange's work include Machine Learning and Algorithms (37 papers), Algorithms and Data Compression (23 papers) and semigroups and automata theory (15 papers). Steffen Lange is often cited by papers focused on Machine Learning and Algorithms (37 papers), Algorithms and Data Compression (23 papers) and semigroups and automata theory (15 papers). Steffen Lange collaborates with scholars based in Germany, Japan and United States. Steffen Lange's co-authors include Tilman Santarius, Johanna Pohl, Thomas Zeugmann, Matthias Schmelzer, Vasilis Kostakis, Barbara Muraca, Giorgos Kallis, Susan Paulson, Sandra Zilles and Rolf Wiehagen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Cleaner Production and Scientific Reports.

In The Last Decade

Steffen Lange

78 papers receiving 2.1k citations

Hit Papers

Digitalization and energy consumption. Does ICT reduce en... 2018 2026 2020 2023 2020 2018 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Digitalization and energy consumption. Does ICT reduce energy demand?
    2020 773 citations Steffen Lange, Johanna Pohl et al. profile →
  2. Research On Degrowth
    2018 360 citations Steffen Lange et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Steffen Lange Germany 20 763 483 454 308 284 88 2.2k
Wei Zhou China 25 406 0.5× 350 0.7× 106 0.2× 271 0.9× 93 0.3× 179 2.4k
Tomáš Havránek Czechia 33 2.2k 2.9× 312 0.6× 327 0.7× 169 0.5× 45 0.2× 113 4.1k
Gang Hao China 23 528 0.7× 77 0.2× 229 0.5× 157 0.5× 44 0.2× 65 1.8k
John S. Liu Taiwan 24 889 1.2× 146 0.3× 94 0.2× 61 0.2× 126 0.4× 52 2.8k
Xuedong Liang China 27 293 0.4× 185 0.4× 48 0.1× 67 0.2× 333 1.2× 110 2.0k
Mohammad Zoynul Abedin United Kingdom 35 1.7k 2.3× 397 0.8× 375 0.8× 17 0.1× 221 0.8× 190 3.4k
David M. Hart United States 25 428 0.6× 563 1.2× 251 0.6× 32 0.1× 384 1.4× 131 2.9k
Louis Y.Y. Lu Taiwan 22 724 0.9× 113 0.2× 96 0.2× 47 0.2× 119 0.4× 43 2.7k
L.S. Ganesh India 25 179 0.2× 188 0.4× 73 0.2× 77 0.3× 133 0.5× 66 2.3k
Lin Zhou China 26 1.5k 1.9× 137 0.3× 130 0.3× 99 0.3× 35 0.1× 90 2.2k

Countries citing papers authored by Steffen Lange

Since Specialization
Citations

This map shows the geographic impact of Steffen Lange's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Steffen Lange with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steffen Lange more than expected).

Fields of papers citing papers by Steffen Lange

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Steffen Lange. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Steffen Lange. The network helps show where Steffen Lange may publish in the future.

Co-authorship network of co-authors of Steffen Lange

This figure shows the co-authorship network connecting the top 25 collaborators of Steffen Lange. A scholar is included among the top collaborators of Steffen Lange based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Steffen Lange. Steffen Lange is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Hond, Anne de, et al.. (2025). When, where, who, what, and why? The five Ws of workflow analysis for implementing an AI decision support tool at the intensive care. Pure Amsterdam UMC. 7. 100095–100095. 2 indexed citations
2.
Lange, Steffen, et al.. (2024). Inflation in Germany: Energy Prices, Profit Shares, and Market Power in Different Sectors. International Journal of Political Economy. 53(4). 342–363.
3.
Lange, Steffen, et al.. (2023). The net climate effect of digitalization, differentiating between firms and households. Energy Economics. 126. 106941–106941. 11 indexed citations
4.
Lange, Steffen, et al.. (2023). The induction effect: why the rebound effect is only half the story of technology's failure to achieve sustainability. SHILAP Revista de lepidopterología. 4. 8 indexed citations
5.
6.
Wetzl, Jens, et al.. (2023). Lazy Luna: Extendible software for multilevel reader comparison in cardiovascular magnetic resonance imaging. Computer Methods and Programs in Biomedicine. 238. 107615–107615. 3 indexed citations
7.
Santarius, Tilman, Jan Bieser, Vivian Frick, et al.. (2022). Digital sufficiency: conceptual considerations for ICTs on a finite planet. Annals of Telecommunications. 78(5-6). 277–295. 42 indexed citations
8.
Lange, Steffen, et al.. (2016). Knowledge Intensive Business Services (KIBS) in the Context of Changing Energy Economics in Germany. SHILAP Revista de lepidopterología. 3 indexed citations
9.
Ziegler, Andreas, et al.. (2007). Logistische Regression. DMW - Deutsche Medizinische Wochenschrift. 132(S 01). e33–e35. 5 indexed citations
10.
Bender, Ralf, et al.. (2007). Vergleich von Messmethoden. DMW - Deutsche Medizinische Wochenschrift. 132(S 01). e69–e73. 46 indexed citations
11.
Lange, Steffen. (2006). Die Rolle randomisierter kontrollierter Studien bei der medizinischen Bewertung von Routineverfahren. Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz. 49(3). 272–277. 2 indexed citations
12.
Lange, Steffen & Sandra Zilles. (2005). Relations between Gold-style learning and query learning. Information and Computation. 203(2). 211–237. 8 indexed citations
13.
Lange, Steffen, et al.. (2003). Advanced elementary formal systems. Theoretical Computer Science. 298(1). 51–70. 2 indexed citations
14.
Jantke, Klaus P., et al.. (2002). Consistency Queries in Information Extraction. 1 indexed citations
15.
Lange, Steffen, et al.. (2001). Learning Approaches to Wrapper Induction. The Florida AI Research Society. 249–253.
16.
Jain, Sanjay, Efim Kinber, Steffen Lange, Rolf Wiehagen, & Thomas Zeugmann. (2000). Learning languages and functions by erasing. Theoretical Computer Science. 241(1-2). 143–189. 2 indexed citations
17.
Case, John, Sanjay Jain, Steffen Lange, & Thomas Zeugmann. (1999). Incremental Concept Learning for Bounded Data Mining. Information and Computation. 152(1). 74–110. 32 indexed citations
18.
Jantke, Klaus P., et al.. (1998). Characterizing Sufficient Expertise for Learning Systems Validation. The Florida AI Research Society. 452–456. 1 indexed citations
19.
Lange, Steffen & Thomas Zeugmann. (1996). Incremental Learning from Positive Data. Journal of Computer and System Sciences. 53(1). 88–103. 42 indexed citations
20.
Lange, Steffen & Rolf Wiehagen. (1990). Polynomial-Time Inference of Pattern Languages.. 289–301.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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