Manolis Sifalakis

903 total citations
44 papers, 512 citations indexed

About

Manolis Sifalakis is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, Manolis Sifalakis has authored 44 papers receiving a total of 512 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Computer Networks and Communications, 21 papers in Electrical and Electronic Engineering and 12 papers in Artificial Intelligence. Recurrent topics in Manolis Sifalakis's work include Advanced Memory and Neural Computing (16 papers), Caching and Content Delivery (10 papers) and Network Traffic and Congestion Control (7 papers). Manolis Sifalakis is often cited by papers focused on Advanced Memory and Neural Computing (16 papers), Caching and Content Delivery (10 papers) and Network Traffic and Congestion Control (7 papers). Manolis Sifalakis collaborates with scholars based in Netherlands, Switzerland and United Kingdom. Manolis Sifalakis's co-authors include Christian Tschudin, Amirreza Yousefzadeh, Federico Corradi, Jan Stuijt, David Hutchison, Stefan Schmid, Marica Amadeo, Claudia Campolo, Antonella Molinaro and Guangzhi Tang and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Journal on Selected Areas in Communications and Neural Networks.

In The Last Decade

Manolis Sifalakis

42 papers receiving 498 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Manolis Sifalakis Netherlands 10 323 175 95 43 39 44 512
Zamshed I. Chowdhury United States 12 164 0.5× 371 2.1× 65 0.7× 17 0.4× 27 0.7× 34 524
H. Ekin Sumbul United States 10 135 0.4× 346 2.0× 118 1.2× 65 1.5× 67 1.7× 24 522
Fei Xia United Kingdom 12 340 1.1× 312 1.8× 42 0.4× 26 0.6× 22 0.6× 102 618
Sai Rahul Chalamalasetti United States 10 178 0.6× 370 2.1× 118 1.2× 48 1.1× 19 0.5× 32 587
Tsung-Te Liu Taiwan 12 70 0.2× 544 3.1× 56 0.6× 39 0.9× 24 0.6× 46 649
Fangyang Shen United States 11 119 0.4× 158 0.9× 106 1.1× 19 0.4× 34 0.9× 38 318
Alex Veidenbaum United States 13 286 0.9× 261 1.5× 73 0.8× 27 0.6× 51 1.3× 61 539
Arindam Mallik Belgium 16 153 0.5× 347 2.0× 40 0.4× 7 0.2× 9 0.2× 41 527
İbrahim Ethem Bağcı United Kingdom 12 166 0.5× 265 1.5× 74 0.8× 82 1.9× 3 0.1× 24 493
Javier Navaridas United Kingdom 16 397 1.2× 402 2.3× 124 1.3× 75 1.7× 61 1.6× 73 728

Countries citing papers authored by Manolis Sifalakis

Since Specialization
Citations

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

Fields of papers citing papers by Manolis Sifalakis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Manolis Sifalakis

This figure shows the co-authorship network connecting the top 25 collaborators of Manolis Sifalakis. A scholar is included among the top collaborators of Manolis Sifalakis 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 Manolis Sifalakis. Manolis Sifalakis 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.
Tang, Guangzhi, et al.. (2025). Event-based optical flow on neuromorphic processor: ANN vs. SNN comparison based on activation sparsification. Neural Networks. 188. 107447–107447. 4 indexed citations
2.
Gebregiorgis, Anteneh, Said Hamdioui, Mario Konijnenburg, et al.. (2024). Optimizing event-based neural networks on digital neuromorphic architecture: a comprehensive design space exploration. Frontiers in Neuroscience. 18. 1335422–1335422. 6 indexed citations
3.
Linares-Barranco, B., et al.. (2024). A tunable multi-timescale Indium-Gallium-Zinc-Oxide thin-film transistor neuron towards hybrid solutions for spiking neuromorphic applications. SHILAP Revista de lepidopterología. 3(1). 102–102. 5 indexed citations
4.
Yousefzadeh, Amirreza, et al.. (2024). Co-optimized training of models with synaptic delays for digital neuromorphic accelerators. University of Twente Research Information. 1–5. 4 indexed citations
5.
Sifalakis, Manolis, et al.. (2024). Neural network-based arterial diameter estimation from ultrasound data. SHILAP Revista de lepidopterología. 3(12). e0000659–e0000659. 1 indexed citations
6.
Tang, Guangzhi, et al.. (2024). SENSIM: An Event-driven Parallel Simulator for Multi-core Neuromorphic Systems. Research Explorer (The University of Manchester). 1–6.
7.
Tang, Guangzhi, et al.. (2024). Benchmarking of hardware-efficient real-time neural decoding in brain–computer interfaces. SHILAP Revista de lepidopterología. 4(2). 24008–24008. 6 indexed citations
8.
Iturbe, Xabier, B. Linares-Barranco, Sio-Hoï Ieng, et al.. (2024). Invited: Neuromorphic Vision Modalities in the NimbleAI 3D Chip. University of Twente Research Information. 1–4.
9.
Sifalakis, Manolis, et al.. (2024). TRIP: Trainable Region-of-Interest Prediction for Hardware-Efficient Neuromorphic Processing on Event-Based Vision. Research Publications (Maastricht University). 94–101. 1 indexed citations
10.
Tang, Guangzhi, et al.. (2023). SENECA: building a fully digital neuromorphic processor, design trade-offs and challenges. Frontiers in Neuroscience. 17. 1187252–1187252. 14 indexed citations
11.
Yousefzadeh, Amirreza & Manolis Sifalakis. (2022). Delta Activation Layer exploits temporal sparsity for efficient embedded video processing. 2022 International Joint Conference on Neural Networks (IJCNN). 1–10. 5 indexed citations
12.
Parnell, Thomas, et al.. (2017). Understanding and optimizing the performance of distributed machine learning applications on apache spark. arXiv (Cornell University). 331–338. 5 indexed citations
13.
Parnell, Thomas, et al.. (2016). High-Performance Distributed Machine Learning using Apache SPARK.. arXiv (Cornell University). 1 indexed citations
14.
Tschudin, Christian & Manolis Sifalakis. (2014). Named functions and cached computations. 851–857. 16 indexed citations
15.
Sifalakis, Manolis, et al.. (2013). CCN & TCP co-existence in the future Internet: Should CCN be compatible to TCP?. Integrated Network Management. 1109–1115. 9 indexed citations
16.
Sifalakis, Manolis, et al.. (2013). A chemical-inspired approach to design distributed rate controllers for packet networks. Integrated Network Management. 1358–1364. 1 indexed citations
17.
Monti, Marco, et al.. (2012). Extending the artificial chemistry to design networking algorithms with controllable dynamics. 4 indexed citations
18.
Schmid, Stefan, et al.. (2006). A highly flexible service composition framework for real-life networks. Computer Networks. 50(14). 2488–2505. 7 indexed citations
19.
Sifalakis, Manolis, Stefan Schmid, & David Hutchison. (2005). Network address hopping a mechanism to enhance data protection for packet communications. 3. 1518–1523. 20 indexed citations
20.
Sifalakis, Manolis, et al.. (2004). Adding reasoning and cognition to the internet. Lancaster EPrints (Lancaster University). 3 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Zamshed I. Chowdhury Breakdown of academic impact, for papers by H. Ekin Sumbul Breakdown of academic impact, for papers by Fei Xia Breakdown of academic impact, for papers by Sai Rahul Chalamalasetti Breakdown of academic impact, for papers by Tsung-Te Liu Breakdown of academic impact, for papers by Fangyang Shen Breakdown of academic impact, for papers by Alex Veidenbaum Breakdown of academic impact, for papers by Arindam Mallik Breakdown of academic impact, for papers by İbrahim Ethem Bağcı Breakdown of academic impact, for papers by Javier Navaridas
Rankless by CCL
2026