---
title: "Denmark — research institutions, scientists and papers"
description: "Denmark: 7 institutions with papers in our library in 3 agglomerations, 38 people with a page, 79 works, 16,666 citations."
canonical: "https://research.elamur.ai/free/en/countries/denmark/"
---
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# Denmark

Country 7 institutions in 3 agglomerations · [all countries](https://md.research.elamur.ai/free/en/countries/)

[**7** institutions with a page](https://md.research.elamur.ai/free/en/countries/denmark/#institutions) · [**3** agglomerations](https://md.research.elamur.ai/free/en/countries/denmark/#agglomerations) · [**38** people with a page](https://md.research.elamur.ai/free/en/countries/denmark/#authors) · [**79** works in our library](https://md.research.elamur.ai/free/en/countries/denmark/#works) · [**16,666** citations of their works](https://md.research.elamur.ai/free/en/countries/denmark/#works)

## About

### Profile

This entry gathers the research institutions in [Denmark](https://md.research.elamur.ai/free/en/orgs/country/dk/) that appear in the library. An institution is included only when its researchers wrote at least two of the papers in our library, so the list reflects the Danish presence in this collection rather than the full Danish research system. It sits alongside comparable entries for other countries and kinds of organisation, all reachable from the general [index of institutions](https://md.research.elamur.ai/free/en/orgs/).

Seven institutions qualify. Five are universities with a broad or specialised academic remit, one is a hospital, and one is a business school organised as a university. They are listed in order of the cited work their scientists produced while affiliated with them, so the order describes their weight in this library, not their size or standing elsewhere. Four places are represented: the capital, Copenhagen, which hosts most of the institutions; Odense; Aalborg; and Kongens Lyngby, north of the capital.

The Danish portion of the library is highly concentrated. One institution accounts for most of the Danish works and citations on this site, a second contributes a clearly smaller but substantial body, and the remaining five each contribute a handful of papers. The sections below describe each institution, how the institutions relate by location and type, and what the pattern suggests about how Danish research shows up in the collection.

### Research strengths

The entry identifies Danish institutions and their place in the library's citation picture. It does not break their output down by field, so any account of strengths has to rest on the kinds of institution involved rather than on topic labels. The institutional mix is still informative.

The largest contributor is a general university, the [University of Copenhagen](https://md.research.elamur.ai/free/en/universities/university-of-copenhagen/). Its body of work in our library is much larger than that of any other Danish institution, and it has gathered by far the most citations. Because it is a comprehensive university, its presence suggests that Danish work in the library spans a wide range rather than one narrow specialty, though the entry does not show which fields dominate.

Second is a specialised institution, the [IT University of Copenhagen](https://md.research.elamur.ai/free/en/universities/it-university-of-copenhagen/). Its name and type point to computing and information technology. Its works here are well cited, which makes it the clearest sign of a technology-oriented strand in the Danish contribution. That a specialised IT university ranks above several broader universities is one of the more distinctive features of the Danish list.

Engineering and technical science appear through the [Technical University of Denmark](https://md.research.elamur.ai/free/en/universities/technical-university-of-denmark/), based in Kongens Lyngby. It contributes only a couple of papers to the library, but they have attracted considerable attention, so its contribution is small in volume and comparatively heavily cited.

Clinical and medical research appears through [Copenhagen University Hospital](https://md.research.elamur.ai/free/en/hospitals/copenhagen-university-hospital/), the only hospital on the list. Like the Technical University of Denmark, it contributes very few papers, but they are cited well beyond what their number would suggest. Among the smaller Danish contributors, its papers stand out for the attention each one has received.

Business, management and the social sciences are represented by [Copenhagen Business School](https://md.research.elamur.ai/free/en/universities/copenhagen-business-school/). Its works in our library are few and have so far drawn modest citation interest compared with the other institutions.

The two remaining universities lie outside the Copenhagen area. The [University of Southern Denmark](https://md.research.elamur.ai/free/en/universities/university-of-southern-denmark/) in Odense and [Aalborg University](https://md.research.elamur.ai/free/en/universities/aalborg-university/) in Aalborg each contribute a small group of papers. Aalborg's works have been cited more often than Odense's, although the University of Southern Denmark is listed above Aalborg University. The list is ordered by a measure of cited work rather than by raw totals, so these differences should not be overinterpreted.

Taken together, the Danish contribution covers general academic research, information technology, engineering, clinical medicine and business studies. Its centre of gravity is clearly the University of Copenhagen, with a strong secondary pole in IT research.

### Leading scientists

The entry lists institutions rather than individual researchers, so it does not name particular Danish scientists. Readers who want the people behind this work can open each institution's own entry in the library, which lists the researchers whose papers in our library carry that affiliation. The University of Copenhagen and the IT University of Copenhagen are the natural starting points, since together they hold most of the Danish works here.

### Landmark works

The entry does not list individual Danish papers. It does show where the most cited Danish work is concentrated. The University of Copenhagen holds the largest share of citations by a wide margin, so most of the influential Danish papers in our library are likely to come from its researchers. The IT University of Copenhagen is the second source of well-cited work. Copenhagen University Hospital and the Technical University of Denmark have each contributed only a pair of papers, but those papers have been cited heavily enough to rank among the more notable Danish contributions relative to their volume. The individual titles and what each found can be traced through the institutions' own entries.

### Collaborations

The entry does not record co-authorship links between institutions or with partners abroad, so it cannot show which Danish institutions work together or which foreign countries they work with most. Geography gives some context, though it is not evidence of joint work. Four of the seven institutions are in Copenhagen: the University of Copenhagen, the IT University of Copenhagen, Copenhagen University Hospital and Copenhagen Business School. The Technical University of Denmark is close by in Kongens Lyngby. A university, a university hospital, a technical university, an IT university and a business school in one metropolitan area makes cross-institutional work at least plausible. Whether it appears in the library's papers can only be seen in the institutions' own entries and in the author lists of their works.

Outside the capital region, the University of Southern Denmark in Odense and Aalborg University in Aalborg extend the Danish presence to other parts of the country. Their contributions are modest in volume, but they show that Danish research in the library is not confined to Copenhagen.

### Geography and institutional mix

The Danish list is weighted heavily toward Copenhagen. The capital hosts the largest contributor, the second largest, the only hospital and the only business school. Adding the Technical University of Denmark at Kongens Lyngby, the Greater Copenhagen area accounts for five of the seven institutions and nearly all of the Danish citation weight in the library.

The mix is also mostly academic. Six of the seven institutions are universities, and the only non-university is a hospital with university links in its name. No companies, government laboratories or independent research institutes from Denmark meet the inclusion threshold, although the library's category for institutions would admit them. On this site, then, Danish research appears almost entirely through universities and academic medicine.

Among the universities, the range runs from comprehensive to specialised. The University of Copenhagen, the University of Southern Denmark and Aalborg University are broad institutions. The Technical University of Denmark, the IT University of Copenhagen and Copenhagen Business School each focus on a defined area: engineering, information technology and business respectively. Specialised institutions sit both near the top and near the bottom of the ordering, so specialisation by itself does not determine how much an institution's work has been cited in this library.

### How the list is ordered

The institutions are ranked by the cited work their scientists did there, not by how many papers they have contributed. This explains some features of the ordering. Copenhagen University Hospital and the Technical University of Denmark contribute fewer papers than Copenhagen Business School or the University of Southern Denmark, yet their papers have been cited much more. The University of Southern Denmark is listed above Aalborg University even though Aalborg's works have drawn more citations, which shows that the ranking measure does not simply follow citation totals.

For readers, the main point is that the two top positions are clear. The University of Copenhagen and the IT University of Copenhagen account for most of the Danish citation weight here. Below them, the five smaller contributors each hold a modest place, and their relative order matters less than their combined presence.

### Over time

The entry does not give publication years for the Danish works, so it cannot show how Danish research in the library has developed over time or which periods were most productive. The figures attached to each institution grow as papers are added to the library, and the ordering may change as new works and citations accumulate. A reader interested in the timeline of a particular institution's research can open its entry, where its works are listed with their details.

As things stand on this site, Danish research is represented by a compact group of institutions centred on Copenhagen. A comprehensive university dominates, a specialised IT university provides a strong second strand, and engineering, clinical medicine, business studies and two regional universities make smaller contributions.

## Where

## Agglomerations (3)

1. [**Copenhagen**5 institutions*16,112 citations*](https://md.research.elamur.ai/free/en/agglomerations/copenhagen/)
2. [**Aalborg**1 institution*449 citations*](https://md.research.elamur.ai/free/en/agglomerations/aalborg/)
3. [**Odense**1 institution*105 citations*](https://md.research.elamur.ai/free/en/agglomerations/odense/)

## Institutions (7)

### 🎓 Universities (6)

**[University of Copenhagen](https://md.research.elamur.ai/free/en/universities/university-of-copenhagen/)**University · [Copenhagen](https://md.research.elamur.ai/free/en/agglomerations/copenhagen/), Denmark*65 works · 12,760 citations*

**[IT University of Copenhagen](https://md.research.elamur.ai/free/en/universities/it-university-of-copenhagen/)**University · [Copenhagen](https://md.research.elamur.ai/free/en/agglomerations/copenhagen/), Denmark*11 works · 1,744 citations*

**[Technical University of Denmark](https://md.research.elamur.ai/free/en/universities/technical-university-of-denmark/)**University · [Kongens Lyngby](https://md.research.elamur.ai/free/en/agglomerations/copenhagen/), Denmark*2 works · 626 citations*

**[Aalborg University](https://md.research.elamur.ai/free/en/universities/aalborg-university/)**University · [Aalborg](https://md.research.elamur.ai/free/en/agglomerations/aalborg/), Denmark*3 works · 449 citations*

**[University of Southern Denmark](https://md.research.elamur.ai/free/en/universities/university-of-southern-denmark/)**University · [Odense](https://md.research.elamur.ai/free/en/agglomerations/odense/), Denmark*3 works · 105 citations*

### 🏥 Hospitals and medical centres (1)

**[Copenhagen University Hospital](https://md.research.elamur.ai/free/en/hospitals/copenhagen-university-hospital/)**Hospital · [Copenhagen](https://md.research.elamur.ai/free/en/agglomerations/copenhagen/), Denmark*2 works · 934 citations*

[See all 7 institutions →](https://md.research.elamur.ai/free/en/countries/denmark/institutions/)

## People (38)

Authors with a page confirmed at its institutions, the most cited first.

[🧑‍🔬**Dirk Hovy** University of Copenhagen 18 papers here · 6,681 citations](https://md.research.elamur.ai/free/en/authors/dirk-hovy/) · [🧑‍🔬**Anders Søgaard** University of Copenhagen 21 papers here · 4,341 citations](https://md.research.elamur.ai/free/en/authors/anders-sogaard/) · [🧑‍🔬**Ilias Chalkidis** University of Copenhagen 8 papers here · 4,076 citations](https://md.research.elamur.ai/free/en/authors/ilias-chalkidis/) · [🧑‍🔬**Isabelle Augenstein** University of Copenhagen 10 papers here · 3,632 citations](https://md.research.elamur.ai/free/en/authors/isabelle-augenstein/) · [🧑‍🔬**Anna Rogers** University of Copenhagen 3 papers here · 3,304 citations](https://md.research.elamur.ai/free/en/authors/anna-rogers/) · [🧑‍🔬**Barbara Plank** IT University of Copenhagen 18 papers here · 3,283 citations](https://md.research.elamur.ai/free/en/authors/barbara-plank/) · [🧑‍🔬**Leon Derczynski** IT University of Copenhagen 6 papers here · 2,650 citations](https://md.research.elamur.ai/free/en/authors/leon-derczynski/) · [🧑‍🔬**Daniel Hershcovich** University of Copenhagen 8 papers here · 1,687 citations](https://md.research.elamur.ai/free/en/authors/daniel-hershcovich/) · [🧑‍🔬**Desmond Elliott** University of Copenhagen 5 papers here · 1,565 citations](https://md.research.elamur.ai/free/en/authors/desmond-elliott/) · [🧑‍🔬**Anuj Pareek** Copenhagen University Hospital 2 papers here · 1,259 citations](https://md.research.elamur.ai/free/en/authors/anuj-pareek/) · [🧑‍🔬**Christina Lioma** University of Copenhagen 3 papers here · 962 citations](https://md.research.elamur.ai/free/en/authors/christina-lioma/) · [🧑‍🔬**Ruixiang Cui** University of Copenhagen 2 papers here · 955 citations](https://md.research.elamur.ai/free/en/authors/ruixiang-cui/)

[See all 38 people →](https://md.research.elamur.ai/free/en/countries/denmark/people/)

## Works in our library (79)

Works of its institutions, the most cited first.

1. [**Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter**Zeerak Waseem, Dirk Hovy*2016 · 2,158 citations*](https://md.research.elamur.ai/free/en/papers/waseem-2016-hateful-symbols-or-hateful-people/)
2. [**A Primer in BERTology: What We Know About How BERT Works**Anna Rogers, Olga Kovaleva, Anna Rumshisky*2020 · 2,127 citations*](https://md.research.elamur.ai/free/en/papers/rogers-2020-primer-bertology-what-we-know/)
3. [**Adapted Large Language Models Can Outperform Medical Experts in Clinical Text Summarization**Dave Van Veen, Cara Van Uden, Louis Blankemeier, et al.*2023 · 925 citations*](https://md.research.elamur.ai/free/en/papers/veen-2023-adapted-large-language-models-outperform/)
4. [**Are You a Racist or Am I Seeing Things? Annotator Influence on Hate Speech Detection on Twitter**Zeerak Waseem*2016 · 760 citations*](https://md.research.elamur.ai/free/en/papers/waseem-2016-are-you-racist-or-am/)
5. [**Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm**Bjarke Felbo, Alan Mislove, Anders Søgaard, et al.*2017 · 617 citations*](https://md.research.elamur.ai/free/en/papers/felbo-2017-millions-emoji-occurrences-learn-any/)
6. [**Deep multi-task learning with low level tasks supervised at lower layers**Anders Søgaard, Yoav Goldberg*2016 · 584 citations*](https://md.research.elamur.ai/free/en/papers/sogaard-2016-deep-multi-task-learning-low/)
7. [**The Social Impact of Natural Language Processing**Dirk Hovy, Shannon L. Spruit*2016 · 516 citations*](https://md.research.elamur.ai/free/en/papers/hovy-2016-social-impact-natural-language-processing/)
8. [**On the Limitations of Unsupervised Bilingual Dictionary Induction**Anders Søgaard, Sebastian Ruder, Ivan Vulić*2018 · 396 citations*](https://md.research.elamur.ai/free/en/papers/sogaard-2018-limitations-unsupervised-bilingual-dictionary-induction/)
9. [**JW300: A Wide-Coverage Parallel Corpus for Low-Resource Languages**Željko Agić, Ivan Vulić*2019 · 373 citations*](https://md.research.elamur.ai/free/en/papers/agic-2019-jw300-wide-coverage-parallel-corpus/)
10. [**Neural Unsupervised Domain Adaptation in NLP–-A Survey**Alan Ramponi, Barbara Plank*2020 · 334 citations*](https://md.research.elamur.ai/free/en/papers/ramponi-2020-neural-unsupervised-domain-adaptation-nlp/)
11. [**MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims**Isabelle Augenstein, Christina Lioma, Dongsheng Wang, et al.*2019 · 318 citations*](https://md.research.elamur.ai/free/en/papers/augenstein-2019-multifc-real-world-multi-domain/)
12. [**Identifying beneficial task relations for multi-task learning in deep neural networks**Joachim Bingel, Anders Søgaard*2017 · 305 citations*](https://md.research.elamur.ai/free/en/papers/bingel-2017-identifying-beneficial-task-relations-multi/)
13. [**SemEval-2019 Task 7: RumourEval, Determining Rumour Veracity and Support for Rumours**Genevieve Gorrell, Elena Kochkina, Maria Liakata, et al.*2019 · 290 citations*](https://md.research.elamur.ai/free/en/papers/gorrell-2019-semeval-2019-task-7-rumoureval/)
14. [**Challenges and Strategies in Cross-Cultural NLP**Daniel Hershcovich, Stella Frank, Heather Lent, et al.*2022 · 290 citations*](https://md.research.elamur.ai/free/en/papers/hershcovich-2022-challenges-strategies-cross-cultural-nlp/)
15. [**Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study**Yong Cao, Li Zhou, Seolhwa Lee, et al.*2023 · 278 citations*](https://md.research.elamur.ai/free/en/papers/cao-2023-assessing-cross-cultural-alignment-between/)
16. [**A Diagnostic Study of Explainability Techniques for Text Classification**Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma, et al.*2020 · 273 citations*](https://md.research.elamur.ai/free/en/papers/atanasova-2020-diagnostic-study-explainability-techniques-text/)
17. [**LexGLUE: A Benchmark Dataset for Legal Language Understanding in English**Ilias Chalkidis; Abhik Jana; Dirk Hartung; Michael Bommarito; Ion Androutsopoulos; Daniel Martin Katz;, Nikolaos Aletras*2021 · 256 citations*](https://md.research.elamur.ai/free/en/papers/chalkidis-2021-lexglue-benchmark-dataset-legal-language/)
18. [**Factuality Challenges in the Era of Large Language Models**Isabelle Augenstein, Timothy Baldwin, Meeyoung Cha, et al.*2023 · 241 citations*](https://md.research.elamur.ai/free/en/papers/augenstein-2023-factuality-challenges-era-large-language/)
19. [**Humanity's Last Exam**Long Phan, Alice Gatti, Ziwen Han, et al.*2025 · 235 citations*](https://md.research.elamur.ai/free/en/papers/phan-2025-humanity-s-last-exam/)
20. [**Findings of the Third Shared Task on Multimodal Machine Translation**Loïc Barrault, Fethi Bougares, Lucia Specia, et al.*2018 · 227 citations*](https://md.research.elamur.ai/free/en/papers/barrault-2018-findings-third-shared-task-multimodal/)
21. [**Generating Fact Checking Explanations**Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma, et al.*2020 · 219 citations*](https://md.research.elamur.ai/free/en/papers/atanasova-2020-generating-fact-checking-explanations/)
22. [**Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning**Shivalika Singh, Freddie Vargus, Daniel D'souza, et al.*2024 · 202 citations*](https://md.research.elamur.ai/free/en/papers/singh-2024-aya-dataset-open-access-collection/)
23. [**Multilingual Part-of-Speech Tagging with Bidirectional Long Short-Term Memory Models and Auxiliary Loss**Barbara Plank, Anders Søgaard, Yoav Goldberg*2016 · 201 citations*](https://md.research.elamur.ai/free/en/papers/plank-2016-multilingual-part-speech-tagging-bidirectional/)
24. [**Multilingual Projection for Parsing Truly Low-Resource Languages**Željko Agić, Anders Johannsen, Barbara Plank, et al.*2016 · 195 citations*](https://md.research.elamur.ai/free/en/papers/agic-2016-multilingual-projection-parsing-truly-low/)
25. [**A Survey on Stance Detection for Mis- and Disinformation Identification**Momchil Hardalov, Arnav Arora, Preslav Nakov, et al.*2022 · 187 citations*](https://md.research.elamur.ai/free/en/papers/hardalov-2022-survey-stance-detection-mis-disinformation/)

[See all 79 works →](https://md.research.elamur.ai/free/en/countries/denmark/works/)

## Topics

Topics of its works in our library, with the number of works on each.

[Multilingual & cross-lingual NLP (11)](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/) · [Sentiment & emotion (10)](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · [Evaluation & benchmarks (7)](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Legal AI (5)](https://md.research.elamur.ai/free/en/topics/legal-ai/) · [Discourse analysis (4)](https://md.research.elamur.ai/free/en/topics/discourse-analysis/) · [Machine translation (4)](https://md.research.elamur.ai/free/en/topics/machine-translation/) · [Universal Dependencies (3)](https://md.research.elamur.ai/free/en/topics/universal-dependencies/) · [Language models & pretraining (3)](https://md.research.elamur.ai/free/en/topics/language-models/) · [Low-resource languages (3)](https://md.research.elamur.ai/free/en/topics/low-resource-languages/) · [Bias, fairness & safety (3)](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Coreference resolution (2)](https://md.research.elamur.ai/free/en/topics/coreference-resolution/) · [Part-of-speech tagging (2)](https://md.research.elamur.ai/free/en/topics/part-of-speech-tagging/) · [Question answering (2)](https://md.research.elamur.ai/free/en/topics/question-answering/) · [Morphology (2)](https://md.research.elamur.ai/free/en/topics/morphology/) · [Reasoning (2)](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Hebrew & Aramaic (2)](https://md.research.elamur.ai/free/en/topics/hebrew-aramaic/) · [Semitic languages (2)](https://md.research.elamur.ai/free/en/topics/semitic-languages/) · [Interpretability (2)](https://md.research.elamur.ai/free/en/topics/interpretability/) · [Vision & language (2)](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Idioms & multiword expressions (2)](https://md.research.elamur.ai/free/en/topics/multiword-expressions/) · [Dependency parsing (1)](https://md.research.elamur.ai/free/en/topics/dependency-parsing/) · [Summarization (1)](https://md.research.elamur.ai/free/en/topics/summarization/) · [Dialogue systems (1)](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Latin (1)](https://md.research.elamur.ai/free/en/topics/latin/) · [Information retrieval & search (1)](https://md.research.elamur.ai/free/en/topics/information-retrieval/) · [Syntax & grammar formalisms (1)](https://md.research.elamur.ai/free/en/topics/syntax-grammar/) · [Historical linguistics & language change (1)](https://md.research.elamur.ai/free/en/topics/language-change/)

## Fields

[Linguistics & languages (45)](https://md.research.elamur.ai/free/en/shelves/linguistics/) · [Natural language processing (45)](https://md.research.elamur.ai/free/en/shelves/nlp/) · [Machine translation (12)](https://md.research.elamur.ai/free/en/shelves/machine-translation/) · [Law (5)](https://md.research.elamur.ai/free/en/shelves/law/) · [AI & machine learning (4)](https://md.research.elamur.ai/free/en/shelves/ai/) · [Mathematics & statistics (1)](https://md.research.elamur.ai/free/en/shelves/mathematics/) · [History & humanities (1)](https://md.research.elamur.ai/free/en/shelves/history/) · [Society & ethics (1)](https://md.research.elamur.ai/free/en/shelves/society/)

## Works by year

2020

- [← back to](https://md.research.elamur.ai/free/en/countries/) — countries