Dimitris Spathis

1.8k total citations
33 papers, 621 citations indexed

About

Dimitris Spathis is a scholar working on Artificial Intelligence, Pulmonary and Respiratory Medicine and Signal Processing. According to data from OpenAlex, Dimitris Spathis has authored 33 papers receiving a total of 621 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 8 papers in Pulmonary and Respiratory Medicine and 8 papers in Signal Processing. Recurrent topics in Dimitris Spathis's work include COVID-19 diagnosis using AI (7 papers), Phonocardiography and Auscultation Techniques (6 papers) and Music and Audio Processing (5 papers). Dimitris Spathis is often cited by papers focused on COVID-19 diagnosis using AI (7 papers), Phonocardiography and Auscultation Techniques (6 papers) and Music and Audio Processing (5 papers). Dimitris Spathis collaborates with scholars based in United Kingdom, Greece and United States. Dimitris Spathis's co-authors include Cecilia Mascolo, Panagiotis Vlamos, Ignacio Perez-Pozuelo, Nicholas J. Wareham, Søren Brage, Andreas Grammenos, Pietro Cicuta, Apinan Hasthanasombat, Xia Tong and Jing Han and has published in prestigious journals such as Journal of Personality and Social Psychology, Scientific Reports and Journal of Medical Internet Research.

In The Last Decade

Dimitris Spathis

32 papers receiving 608 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dimitris Spathis United Kingdom 14 216 127 122 120 101 33 621
Jagmohan Chauhan United Kingdom 13 152 0.7× 78 0.6× 116 1.0× 245 2.0× 78 0.8× 35 634
Otilia Kocsis Greece 13 151 0.7× 46 0.4× 80 0.7× 35 0.3× 42 0.4× 39 476
Himadri Mukherjee India 12 315 1.5× 76 0.6× 134 1.1× 136 1.1× 202 2.0× 49 643
Ting Dang Australia 10 133 0.6× 47 0.4× 53 0.4× 151 1.3× 49 0.5× 43 361
Ascensión Gallardo-Antolín Spain 16 394 1.8× 27 0.2× 119 1.0× 290 2.4× 25 0.2× 59 716
Sudip Vhaduri United States 20 43 0.2× 94 0.7× 129 1.1× 210 1.8× 17 0.2× 45 785
Álvaro Alesanco Spain 18 153 0.7× 19 0.1× 159 1.3× 105 0.9× 32 0.3× 53 889
Laura Verde Italy 13 261 1.2× 76 0.6× 17 0.1× 187 1.6× 50 0.5× 37 490
Nelson Wong United States 13 85 0.4× 50 0.4× 196 1.6× 43 0.4× 51 0.5× 25 823
Sara Colantonio Italy 12 97 0.4× 50 0.4× 161 1.3× 12 0.1× 121 1.2× 75 508

Countries citing papers authored by Dimitris Spathis

Since Specialization
Citations

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

Fields of papers citing papers by Dimitris Spathis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dimitris Spathis

This figure shows the co-authorship network connecting the top 25 collaborators of Dimitris Spathis. A scholar is included among the top collaborators of Dimitris Spathis 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 Dimitris Spathis. Dimitris Spathis 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.
Constantinides, Marios, et al.. (2026). (Un)fair devices: Moving beyond AI accuracy in personal sensing. arXiv (Cornell University).
2.
Saeed, Aaqib, et al.. (2025). Learning under label noise through few-shot human-in-the-loop refinement. Scientific Reports. 15(1). 4276–4276. 2 indexed citations
3.
Spathis, Dimitris, et al.. (2024). CroSSL: Cross-modal Self-Supervised Learning for Time-series through Latent Masking. 152–160. 7 indexed citations
4.
Dang, Ting, et al.. (2024). StatioCL : Contrastive Learning for Time Series via Non-Stationary and Temporal Contrast. 2575–2584. 2 indexed citations
5.
Spathis, Dimitris, et al.. (2024). OptiBreathe: An Earable-based PPG System for Continuous Respiration Rate, Breathing Phase, and Tidal Volume Monitoring. ePrints Soton (University of Southampton). 99–106. 6 indexed citations
6.
Spathis, Dimitris, et al.. (2024). FairComp: 2nd International Workshop on Fairness and Robustness in Machine Learning for Ubiquitous Computing. VBN Forskningsportal (Aalborg Universitet). 996–999. 1 indexed citations
7.
Spathis, Dimitris, et al.. (2024). Using Self-supervised Learning Can Improve Model Fairness. 3942–3953. 1 indexed citations
8.
Spathis, Dimitris & Fahim Kawsar. (2024). The first step is the hardest: pitfalls of representing and tokenizing temporal data for large language models. Journal of the American Medical Informatics Association. 31(9). 2151–2158. 8 indexed citations
9.
Han, Jing, Marco Montagna, Andreas Grammenos, et al.. (2023). Evaluating Listening Performance for COVID-19 Detection by Clinicians and Machine Learning: Comparative Study. Journal of Medical Internet Research. 25. e44804–e44804. 3 indexed citations
10.
Dang, Ting, Jing Han, Xia Tong, et al.. (2023). Conditional Neural ODE Processes for Individual Disease Progression Forecasting: A Case Study on COVID-19. ePrints Soton (University of Southampton). 3914–3925. 4 indexed citations
11.
Bergler, Christian, Maurice Gerczuk, Chloë Brown, et al.. (2023). A summary of the ComParE COVID-19 challenges. Frontiers in Digital Health. 5. 1058163–1058163. 7 indexed citations
12.
Spathis, Dimitris, Ignacio Perez-Pozuelo, Tomas I. Gonzales, et al.. (2022). Longitudinal cardio-respiratory fitness prediction through wearables in free-living environments. npj Digital Medicine. 5(1). 176–176. 11 indexed citations
13.
Dang, Ting, Jing Han, Xia Tong, et al.. (2022). Exploring Longitudinal Cough, Breath, and Voice Data for COVID-19 Progression Prediction via Sequential Deep Learning: Model Development and Validation. Journal of Medical Internet Research. 24(6). e37004–e37004. 23 indexed citations
14.
Greenberg, David M., et al.. (2022). Universals and variations in musical preferences: A study of preferential reactions to Western music in 53 countries.. Journal of Personality and Social Psychology. 122(2). 286–309. 24 indexed citations
15.
Han, Jing, Xia Tong, Dimitris Spathis, et al.. (2022). Sounds of COVID-19: exploring realistic performance of audio-based digital testing. npj Digital Medicine. 5(1). 16–16. 59 indexed citations
16.
Spathis, Dimitris, et al.. (2022). Breaking away from labels: The promise of self-supervised machine learning in intelligent health. Patterns. 3(2). 100410–100410. 22 indexed citations
17.
Hasthanasombat, Apinan, et al.. (2022). Investigating Domain-agnostic Performance in Activity Recognition using Accelerometer Data. University of Birmingham Research Portal (University of Birmingham). 329–334. 1 indexed citations
18.
Perez-Pozuelo, Ignacio, et al.. (2021). Digital phenotyping and sensitive health data: Implications for data governance. Journal of the American Medical Informatics Association. 28(9). 2002–2008. 13 indexed citations
19.
Tong, Xia, Dimitris Spathis, Andreas Grammenos, et al.. (2021). COVID-19 Sounds: A Large-Scale Audio Dataset for Digital Respiratory Screening. Neural Information Processing Systems. 28 indexed citations
20.
Han, Jing, Chloë Brown, Jagmohan Chauhan, et al.. (2021). Exploring Automatic COVID-19 Diagnosis via Voice and Symptoms from Crowdsourced Data. arXiv (Cornell University). 63 indexed citations

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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