Ivan Fernandez

680 total citations
21 papers, 308 citations indexed

About

Ivan Fernandez is a scholar working on Hardware and Architecture, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Ivan Fernandez has authored 21 papers receiving a total of 308 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Hardware and Architecture, 11 papers in Artificial Intelligence and 10 papers in Computer Networks and Communications. Recurrent topics in Ivan Fernandez's work include Parallel Computing and Optimization Techniques (11 papers), Advanced Data Storage Technologies (9 papers) and Time Series Analysis and Forecasting (6 papers). Ivan Fernandez is often cited by papers focused on Parallel Computing and Optimization Techniques (11 papers), Advanced Data Storage Technologies (9 papers) and Time Series Analysis and Forecasting (6 papers). Ivan Fernandez collaborates with scholars based in Spain, Switzerland and Greece. Ivan Fernandez's co-authors include Juan Gómez-Luna, Onur Mutlu, Christina Giannoula, Geraldo F. Oliveira, Izzat El Hajj, Georgios Goumas, Nectarios Koziris, Lois Orosa, Óscar Plata and Mohammad Sadrosadati and has published in prestigious journals such as IEEE Access, Genomics and ACM SIGMETRICS Performance Evaluation Review.

In The Last Decade

Ivan Fernandez

19 papers receiving 282 citations

Peers

Ivan Fernandez

CNC

EEE

CVPR

Christina Giannoula Greece

Geraldo F. Oliveira Switzerland

Licheng Guo United States

Muhammad Ali Shami Sweden

Jason Lau United States

Hyunsung Shin South Korea

Zhaoshi Li China

Lois Orosa Switzerland

Pengcheng Yao China

Samy Meftali France

Christina Giannoula Greece

Ivan Fernandez

130 ×0.9

109 ×0.8

CNC

99 ×0.8

EEE

47 ×0.7

31 ×0.8

CVPR

Citations per year, relative to Ivan Fernandez Ivan Fernandez (= 1×) peers Christina Giannoula

Countries citing papers authored by Ivan Fernandez

Since Specialization

Citations

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

Fields of papers citing papers by Ivan Fernandez

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ivan Fernandez

This figure shows the co-authorship network connecting the top 25 collaborators of Ivan Fernandez. A scholar is included among the top collaborators of Ivan Fernandez 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 Ivan Fernandez. Ivan Fernandez is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Giannoula, Christina, Ivan Fernandez, Jiacheng Yang, et al.. (2025). PyGim: An Efficient Graph Neural Network Library for Real Processing-In-Memory Architectures. ACM SIGMETRICS Performance Evaluation Review. 53(1). 154–156.

Giannoula, Christina, Ivan Fernandez, Jiacheng Yang, et al.. (2024). PyGim : An Efficient Graph Neural Network Library for Real Processing-In-Memory Architectures. Proceedings of the ACM on Measurement and Analysis of Computing Systems. 8(3). 1–36. 1 indexed citations

Fernandez, Ivan, et al.. (2024). A Survey on Privacy Attacks Against Digital Twin Systems in AI-Robotics. 70–79.

Fernandez, Ivan, et al.. (2024). Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunities. IEEE Access. 12. 22072–22097. 12 indexed citations

Fernandez, Ivan, Christina Giannoula, Nika Mansouri Ghiasi, et al.. (2024). MATSA: An MRAM-Based Energy-Efficient Accelerator for Time Series Analysis. IEEE Access. 12. 36727–36742. 4 indexed citations

Espinosa, Elena, et al.. (2023). Comparing assembly strategies for third-generation sequencing technologies across different genomes. Genomics. 115(5). 110700–110700. 9 indexed citations

Fernandez, Ivan, et al.. (2023). Time series analysis acceleration with advanced vectorization extensions. The Journal of Supercomputing. 79(9). 10178–10207. 3 indexed citations

Giannoula, Christina, Ivan Fernandez, Juan Gómez-Luna, et al.. (2022). SparseP: Efficient Sparse Matrix Vector Multiplication on Real Processing-In-Memory Architectures. 288–291. 8 indexed citations

Giannoula, Christina, Ivan Fernandez, Juan Gómez-Luna, et al.. (2022). SparseP. Proceedings of the ACM on Measurement and Analysis of Computing Systems. 6(1). 1–49. 49 indexed citations

10.

Fernandez, Ivan, Christina Giannoula, Mohammed Alser, et al.. (2022). Exploiting Near-Data Processing to Accelerate Time Series Analysis. 106. 279–282. 1 indexed citations

11.

Fernandez, Ivan, et al.. (2022). A Temporal Anomaly Detection System for Vehicles utilizing Functional Working Groups and Sensor Channels. 99–108. 3 indexed citations

12.

Gómez-Luna, Juan, Izzat El Hajj, Ivan Fernandez, et al.. (2022). Benchmarking a New Paradigm: Experimental Analysis and Characterization of a Real Processing-in-Memory System. IEEE Access. 10. 52565–52608. 89 indexed citations

13.

Fernandez, Ivan, et al.. (2022). TraTSA: A Transprecision Framework for Efficient Time Series Analysis. Journal of Computational Science. 63. 101784–101784. 1 indexed citations

14.

Ghiasi, Nika Mansouri, Nandita Vijaykumar, Geraldo F. Oliveira, et al.. (2022). ALP: Alleviating CPU-Memory Data Movement Overheads in Memory-Centric Systems. IEEE Transactions on Emerging Topics in Computing. 11(2). 388–403. 5 indexed citations

15.

Giannoula, Christina, Ivan Fernandez, Juan Gómez-Luna, et al.. (2022). Towards Efficient Sparse Matrix Vector Multiplication on Real Processing-In-Memory Architectures. ACM SIGMETRICS Performance Evaluation Review. 50(1). 33–34. 15 indexed citations

16.

Fernandez, Ivan, et al.. (2022). Exploiting Vector Extensions to Accelerate Time Series Analysis. Repositorio Institucional de la Universidad de Málaga (University of Málaga). 2012 3112. 55–62. 2 indexed citations

17.

Oliveira, Geraldo F., Juan Gómez-Luna, Lois Orosa, et al.. (2021). DAMOV: A New Methodology and Benchmark Suite for Evaluating Data Movement Bottlenecks. Repository for Publications and Research Data (ETH Zurich). 48 indexed citations

18.

Fernandez, Ivan, et al.. (2021). Enabling fast and energy-efficient FM-index exact matching using processing-near-memory. The Journal of Supercomputing. 77(9). 10226–10251. 9 indexed citations

19.

Fernandez, Ivan, et al.. (2020). NATSA: A Near-Data Processing Accelerator for Time Series Analysis.. Repositorio Institucional de la Universidad de Málaga (University of Málaga). 39 indexed citations

20.

Fernandez, Ivan, et al.. (2019). Accelerating time series motif discovery in the Intel Xeon Phi KNL processor. The Journal of Supercomputing. 75(11). 7053–7075. 6 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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