Maja Ercegovac

654 citations
20 papers · 459 indexed · 1 hit paper · h-index 7
Topics
Lung Cancer Diagnosis and Treatment (7 papers)Lung Cancer Treatments and Mutations (5 papers)Chronic Obstructive Pulmonary Disease (COPD) Research (4 papers)
Partner nations
SerbiaAustriaDenmark

In The Last Decade

Maja Ercegovac

17 papers receiving 437 citations

Hit Papers

Trading Accuracy for Power with an Underdesigned Multipli...20112026201620212011100200300

Peers

Maja Ercegovac
Comparison fields: 5 of 49
  • Electrical and Electronic Engineering 353
  • Hardware and Architecture 146
  • Biomedical Engineering 109
  • Computational Theory and Mathematics 66
  • Pulmonary and Respiratory Medicine 54
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Brian Howard United States
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Maja Ercegovac relative to Tae Woo Oh South Korea Tae Woo Oh's profile →
Citations per field
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Tae Woo Oh · 1×
Citations per year

Countries citing papers authored by Maja Ercegovac

Since Specialization
Citations

This map shows the geographic impact of Maja Ercegovac'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 Maja Ercegovac with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maja Ercegovac more than expected).

Fields of papers citing papers by Maja Ercegovac

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maja Ercegovac. 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 Maja Ercegovac. The network helps show where Maja Ercegovac may publish in the future.

Co-authorship network of co-authors of Maja Ercegovac

This figure shows the co-authorship network connecting the top 25 collaborators of Maja Ercegovac. A scholar is included among the top collaborators of Maja Ercegovac 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 Maja Ercegovac. Maja Ercegovac 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
#WorkIndexed citations
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7 2
8 1
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11 19
12 6
13 9
14
Trading Accuracy for Power with an Underdesigned Multiplier Architecturebreakdown →
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15 10
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17 1
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About Maja Ercegovac

Maja Ercegovac is a scholar working on Pulmonary and Respiratory Medicine, Cultural Studies and Visual Arts and Performing Arts, having authored 20 papers that have together received 459 indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (7 papers), Lung Cancer Treatments and Mutations (5 papers) and Chronic Obstructive Pulmonary Disease (COPD) Research (4 papers). The work is most often cited by research in Hardware and Architecture (146 citations), Electrical and Electronic Engineering (353 citations) and Computational Theory and Mathematics (66 citations). Maja Ercegovac has collaborated with scholars based in Serbia, Austria and Denmark. Frequent co-authors include Parag Kulkarni, Puneet Gupta, Jelena Stojšić, Dragan Subotic, Vladimir Žugić, Dušan Trpinac, Branislava Milenković, Milan Gajić, Gordana Radosavljević and Dragica Pešut. Their work appears in journals such as CHEST Journal, Cancers and Microscopy Research and Technique.

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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