Dimitrios Rodopoulos

607 total citations
34 papers, 326 citations indexed

About

Dimitrios Rodopoulos is a scholar working on Electrical and Electronic Engineering, Hardware and Architecture and Computer Networks and Communications. According to data from OpenAlex, Dimitrios Rodopoulos has authored 34 papers receiving a total of 326 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Electrical and Electronic Engineering, 11 papers in Hardware and Architecture and 4 papers in Computer Networks and Communications. Recurrent topics in Dimitrios Rodopoulos's work include Advanced Memory and Neural Computing (11 papers), Radiation Effects in Electronics (10 papers) and Semiconductor materials and devices (10 papers). Dimitrios Rodopoulos is often cited by papers focused on Advanced Memory and Neural Computing (11 papers), Radiation Effects in Electronics (10 papers) and Semiconductor materials and devices (10 papers). Dimitrios Rodopoulos collaborates with scholars based in Greece, Belgium and Netherlands. Dimitrios Rodopoulos's co-authors include Francky Catthoor, Dimitrios Soudris, David Atienza, Tobias G. Noll, Mohamed M. Sabry, Tobias Gemmeke, Peter Debacker, Apostolos Papanikolaou, Chris Van Hoof and Dwaipayan Biswas and has published in prestigious journals such as ACM Computing Surveys, IEEE Transactions on Parallel and Distributed Systems and Advanced Engineering Materials.

In The Last Decade

Dimitrios Rodopoulos

32 papers receiving 320 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dimitrios Rodopoulos Greece 9 187 52 49 48 44 34 326
Kyung Ki Kim United States 10 274 1.5× 53 1.0× 65 1.3× 47 1.0× 45 1.0× 64 373
Nabamita Deb India 10 126 0.7× 77 1.5× 76 1.6× 10 0.2× 27 0.6× 33 332
Luke Everson United States 9 160 0.9× 73 1.4× 251 5.1× 28 0.6× 34 0.8× 21 451
Nevena Ackovska North Macedonia 8 46 0.2× 25 0.5× 68 1.4× 21 0.4× 23 0.5× 50 252
Deepak Kadetotad United States 11 292 1.6× 70 1.3× 63 1.3× 44 0.9× 103 2.3× 26 442
Dennis Walter Germany 11 255 1.4× 42 0.8× 63 1.3× 53 1.1× 25 0.6× 25 332
Naveed Khan Baloch Pakistan 11 96 0.5× 15 0.3× 21 0.4× 47 1.0× 88 2.0× 19 334
Adel Soudani Saudi Arabia 10 97 0.5× 46 0.9× 36 0.7× 17 0.4× 19 0.4× 49 277
Rami A. Abdallah United States 10 350 1.9× 28 0.5× 159 3.2× 101 2.1× 42 1.0× 22 439
Rajesh C. Panicker Singapore 8 81 0.4× 252 4.8× 47 1.0× 17 0.4× 25 0.6× 19 375

Countries citing papers authored by Dimitrios Rodopoulos

Since Specialization
Citations

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

Fields of papers citing papers by Dimitrios Rodopoulos

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dimitrios Rodopoulos

This figure shows the co-authorship network connecting the top 25 collaborators of Dimitrios Rodopoulos. A scholar is included among the top collaborators of Dimitrios Rodopoulos 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 Dimitrios Rodopoulos. Dimitrios Rodopoulos 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.
2.
Mei, Linyan, et al.. (2019). Sub-Word Parallel Precision-Scalable MAC Engines for Efficient Embedded DNN Inference. Lirias (KU Leuven). 6–10. 27 indexed citations
3.
Everson, Luke, Dwaipayan Biswas, Madhuri Panwar, et al.. (2018). BiometricNet: Deep Learning based Biometric Identification using Wrist-Worn PPG. 1–5. 44 indexed citations
4.
Rodopoulos, Dimitrios, Ioannis Sourdis, Zaid Al-Ars, et al.. (2017). BrainFrame: a node-level heterogeneous accelerator platform for neuron simulations. Journal of Neural Engineering. 14(6). 66008–66008. 13 indexed citations
5.
Rodopoulos, Dimitrios, et al.. (2017). Energy Efficient Adaptive Approach for Dependable Performance in the presence of Timing Interference. 209–214. 1 indexed citations
6.
7.
Rodopoulos, Dimitrios, et al.. (2017). Optimizing Extended Hodgkin-Huxley Neuron Model Simulations for a Xeon/Xeon Phi Node. IEEE Transactions on Parallel and Distributed Systems. 28(9). 2581–2594. 4 indexed citations
8.
Rodopoulos, Dimitrios, et al.. (2017). Runtime Slack Creation for Processor Performance Variability using System Scenarios. ACM Transactions on Design Automation of Electronic Systems. 23(2). 1–23. 1 indexed citations
9.
Mallik, A., Daniele Garbin, A. Fantini, et al.. (2017). Design-technology co-optimization for OxRRAM-based synaptic processing unit. T178–T179. 23 indexed citations
10.
Rodopoulos, Dimitrios, et al.. (2016). First impressions from detailed brain model simulations on a Xeon/Xeon-Phi node. Data Archiving and Networked Services (DANS). 361–364. 3 indexed citations
11.
Rodopoulos, Dimitrios, et al.. (2016). Performance analysis of accelerated biophysically-meaningful neuron simulations. Data Archiving and Networked Services (DANS). 83. 1–11. 5 indexed citations
12.
Weckx, Pieter, et al.. (2016). Accuracy of Quasi-Monte Carlo technique in failure probability estimations. 1–4. 1 indexed citations
13.
Stamoulis, Dimitrios, Dimitrios Rodopoulos, Brett H. Meyer, et al.. (2015). Efficient Reliability Analysis of Processor Datapath using Atomistic BTI Variability Models. 57–62. 4 indexed citations
14.
Rodopoulos, Dimitrios, Apostolos Papanikolaou, Francky Catthoor, & Dimitrios Soudris. (2014). Demonstrating HW–SW Transient Error Mitigation on the Single-Chip Cloud Computer Data Plane. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 23(3). 507–519. 5 indexed citations
15.
Stamoulis, Dimitrios, Dimitrios Rodopoulos, Brett H. Meyer, Dimitrios Soudris, & Željko Žilić. (2014). Linear regression techniques for efficient analysis of transistor variability. 16. 267–270. 1 indexed citations
16.
Rodopoulos, Dimitrios, Francky Catthoor, & Dimitrios Soudris. (2014). Tackling Performance Variability Due to RAS Mechanisms with PID-Controlled DVFS. IEEE Computer Architecture Letters. 14(2). 156–159. 11 indexed citations
17.
Rodopoulos, Dimitrios, et al.. (2014). Atomistic Pseudo-Transient BTI Simulation With Inherent Workload Memory. IEEE Transactions on Device and Materials Reliability. 14(2). 704–714. 17 indexed citations
18.
Rodopoulos, Dimitrios, et al.. (2013). Hypervised transient SPICE simulations of large netlists & workloads on multi-processor systems. Design, Automation, and Test in Europe. 655–658. 3 indexed citations
19.
Rodopoulos, Dimitrios, Apostolos Papanikolaou, Francky Catthoor, & Dimitrios Soudris. (2012). Software mitigation of transient errors on the single-chip cloud computer. 1 indexed citations
20.
Rodopoulos, Dimitrios, B. Kaczer, Francky Catthoor, et al.. (2011). Time and workload dependent device variability in circuit simulations. DSpace - NTUA (National Technical University of Athens). 1–4. 26 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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