Szymon Fedor

2.5k total citations · 1 hit paper
31 papers, 1.6k citations indexed

About

Szymon Fedor is a scholar working on Experimental and Cognitive Psychology, Computer Networks and Communications and Electrical and Electronic Engineering. According to data from OpenAlex, Szymon Fedor has authored 31 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Experimental and Cognitive Psychology, 9 papers in Computer Networks and Communications and 7 papers in Electrical and Electronic Engineering. Recurrent topics in Szymon Fedor's work include Mental Health Research Topics (8 papers), Energy Efficient Wireless Sensor Networks (6 papers) and Context-Aware Activity Recognition Systems (6 papers). Szymon Fedor is often cited by papers focused on Mental Health Research Topics (8 papers), Energy Efficient Wireless Sensor Networks (6 papers) and Context-Aware Activity Recognition Systems (6 papers). Szymon Fedor collaborates with scholars based in United States, Ireland and Portugal. Szymon Fedor's co-authors include Rosalind W. Picard, Matthew K. Nock, Evan M. Kleiman, Jeff C. Huffman, Brianna J. Turner, Eleanor E. Beale, Natasha Jaques, Sara Taylor, Akane Sano and Martin Collier and has published in prestigious journals such as New England Journal of Medicine, Journal of Abnormal Psychology and IEEE Communications Surveys & Tutorials.

In The Last Decade

Szymon Fedor

31 papers receiving 1.6k citations

Hit Papers

Examination of real-time fluctuations in suicidal ideatio... 2017 2026 2020 2023 2017 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Szymon Fedor United States 15 656 553 382 300 266 31 1.6k
Jochen Fahrenberg Germany 21 622 0.9× 673 1.2× 430 1.1× 348 1.2× 360 1.4× 84 2.9k
Andrew Raij United States 24 79 0.1× 290 0.5× 301 0.8× 433 1.4× 244 0.9× 52 2.5k
Matthew S. Goodwin United States 33 572 0.9× 458 0.8× 463 1.2× 1.9k 6.5× 199 0.7× 103 3.2k
Akane Sano United States 24 246 0.4× 1.5k 2.8× 358 0.9× 757 2.5× 620 2.3× 80 2.7k
Martti T. Tuomisto Finland 23 463 0.7× 350 0.6× 245 0.6× 437 1.5× 130 0.5× 70 2.0k
Gennaro Tartarisco Italy 22 342 0.5× 144 0.3× 202 0.5× 689 2.3× 114 0.4× 84 1.7k
Nicholas Cummins Germany 31 254 0.4× 1.7k 3.1× 712 1.9× 527 1.8× 308 1.2× 119 3.3k
Oscar Mayora Italy 21 119 0.2× 580 1.0× 112 0.3× 154 0.5× 582 2.2× 87 1.8k
Loe Feijs Netherlands 26 100 0.2× 232 0.4× 271 0.7× 348 1.2× 108 0.4× 174 2.2k
Mashfiqui Rabbi United States 17 118 0.2× 429 0.8× 134 0.4× 226 0.8× 644 2.4× 31 1.7k

Countries citing papers authored by Szymon Fedor

Since Specialization
Citations

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

Fields of papers citing papers by Szymon Fedor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Szymon Fedor

This figure shows the co-authorship network connecting the top 25 collaborators of Szymon Fedor. A scholar is included among the top collaborators of Szymon Fedor 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 Szymon Fedor. Szymon Fedor 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.
Fedor, Szymon, et al.. (2023). Wearable Technology in Clinical Practice for Depressive Disorder. New England Journal of Medicine. 389(26). 2457–2466. 25 indexed citations
2.
Clay, Ieuan, Francesca Cormack, Szymon Fedor, et al.. (2022). Measuring Health-Related Quality of Life With Multimodal Data: Viewpoint. Journal of Medical Internet Research. 24(5). e35951–e35951. 5 indexed citations
3.
Coppersmith, Daniel D.L., Shirley B. Wang, Evan M. Kleiman, et al.. (2022). Real-time digital monitoring of a suicide attempt by a hospital patient. General Hospital Psychiatry. 80. 35–39. 7 indexed citations
4.
Pedrelli, Paola, Szymon Fedor, Asma Ghandeharioun, et al.. (2020). Monitoring Changes in Depression Severity Using Wearable and Mobile Sensors. Frontiers in Psychiatry. 11. 584711–584711. 83 indexed citations
5.
Kleiman, Evan M., et al.. (2018). Negative affect is more strongly associated with suicidal thinking among suicidal patients with borderline personality disorder than those without. Journal of Psychiatric Research. 104. 198–201. 32 indexed citations
6.
Kleiman, Evan M., Brianna J. Turner, Szymon Fedor, et al.. (2017). Examination of real-time fluctuations in suicidal ideation and its risk factors: Results from two ecological momentary assessment studies.. Journal of Abnormal Psychology. 126(6). 726–738. 540 indexed citations breakdown →
7.
Ghandeharioun, Asma, Szymon Fedor, Dawn F. Ionescu, et al.. (2017). Objective assessment of depressive symptoms with machine learning and wearable sensors data. 325–332. 72 indexed citations
8.
Sitanayah, Lanny, Cormac J. Sreenan, & Szymon Fedor. (2016). A Cooja-Based Tool for Coverage and Lifetime Evaluation in an In-Building Sensor Network. Journal of Sensor and Actuator Networks. 5(1). 4–4. 14 indexed citations
9.
Picard, Rosalind W., et al.. (2015). Multiple Arousal Theory and Daily-Life Electrodermal Activity Asymmetry. Emotion Review. 8(1). 62–75. 193 indexed citations
10.
Sreenan, Cormac J., et al.. (2015). A visual programming framework for wireless sensor networks in smart home applications. 28 indexed citations
11.
Picard, Rosalind W., et al.. (2015). Response to Commentaries on “Multiple Arousal Theory and Daily-Life Electrodermal Activity Asymmetry”. Emotion Review. 8(1). 84–86. 9 indexed citations
12.
Chen, Weixuan, Natasha Jaques, Sara Taylor, et al.. (2015). Wavelet-based motion artifact removal for electrodermal activity. PubMed. 2015. 6223–6226. 47 indexed citations
13.
Hossain, A. K. M. Mahtab, Cormac J. Sreenan, & Szymon Fedor. (2014). A Neighbour Disjoint Multipath Scheme for Fault Tolerant Wireless Sensor Networks. Cork Open Research Archive (University College Cork, Ireland). 2571. 308–315. 1 indexed citations
14.
Pacull, François, et al.. (2013). Self-organisation for Building Automation Systems: Middleware LINC as an Integration Tool. Zenodo (CERN European Organization for Nuclear Research). 7726–7732. 12 indexed citations
15.
Jara, Antonio J., et al.. (2013). Service Discovery Protocols for Constrained Machine-to-Machine Communications. IEEE Communications Surveys & Tutorials. 16(1). 41–60. 44 indexed citations
16.
Pesch, Dirk, et al.. (2012). Constrained Application Protocol for Low Power Embedded Networks: A Survey. 38 indexed citations
17.
Fedor, Szymon, Martin Collier, & Cormac J. Sreenan. (2011). Cross-layer routing and time synchronisation in wireless sensor networks. International Journal of Sensor Networks. 10(3). 143–143. 11 indexed citations
19.
Fedor, Szymon & Martin Collier. (2008). Synchronization Service Integrated into Routing Layer in Wireless Sensor Networks. 2905–2910. 5 indexed citations
20.
Fedor, Szymon & Martin Collier. (2007). On the Problem of Energy Efficiency of Multi-Hop vs One-Hop Routing in Wireless Sensor Networks. 380–385. 41 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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