Andreas Spanias

431 papers receiving 5.8k citations

Andreas Spanias's Hit Papers

Attend and Diagnose: Clinical Time Series Analysis Using Attention Models 2018 · 273 citations
2730+2+5Years since publication50100150200250

Peers

Andreas Spanias
Comparison fields: 5 of 156
  • Signal Processing 2.0k
  • Architecture 118
  • Media Technology 580
  • Computer Vision and Pattern Recognition 1.3k
  • Artificial Intelligence 1.8k
Replace Graham C. Goodwin with:
Graham C. Goodwin Australia
Björn Wittenmark Sweden
Yuan Zhuang China
Ying He China
Michael Georgiopoulos United States
Emil M. Petriu Canada
Sergios Theodoridis Greece
Gary Bishop United States
Naresh K. Sinha Canada
Robi Polikar United States
Andreas Spanias relative to Graham C. Goodwin Australia Graham C. Goodwin's profile →
Citations per field
00.5×4.4×
Graham C. Goodwin · 1×
Citations per year

Countries citing papers authored by Andreas Spanias

Since Specialization
Citations

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

Fields of papers citing papers by Andreas Spanias

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Andreas Spanias, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Andreas Spanias Line = papers co-authored together Andreas Spanias links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 461 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2000487
2
Attend and Diagnose: Clinical Time Series Analysis Using Attention Models
Hit paper breakdown →
2018273
3 1994246
4 2017179
5 2002142
6 2010136
7 1999124
8 2005123
9 2012113
10 2002102
11 200490
12 200887
13 200279
14 200572
15 201772
16 199167
17 199667
18 201362
19 201661
20 200959

About Andreas Spanias

Andreas Spanias is a scholar working on Signal Processing, Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Mechanics and Electrical and Electronic Engineering, having authored 461 papers that have together received 6.2k indexed citations. Recurring topics across this work include Speech and Audio Processing (110 papers), Advanced Adaptive Filtering Techniques (75 papers), Experimental Learning in Engineering (57 papers), Advanced Data Compression Techniques (39 papers), Music and Audio Processing (37 papers), Speech Recognition and Synthesis (36 papers), Blind Source Separation Techniques (35 papers) and Sparse and Compressive Sensing Techniques (28 papers). The work is most often cited by research in Signal Processing (2.0k citations), Architecture (118 citations), Media Technology (580 citations), Computer Vision and Pattern Recognition (1.3k citations) and Artificial Intelligence (1.8k citations). Andreas Spanias has collaborated with scholars based in United States, Sweden and Cyprus. Frequent co-authors include Ted Painter, Cihan Tepedelenlioğlu, Jayaraman J. Thiagarajan, Mahesh K. Banavar, J. Foutz, Karthikeyan Natesan Ramamurthy, Visar Berisha, Venkatraman Atti, Huan Song and Deepta Rajan. Their work appears in journals such as IEEE Transactions on Signal Processing, The Journal of the Acoustical Society of America, IEEE Access, IEEE Transactions on Speech and Audio Processing and IEEE Signal Processing Letters.

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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