G. Seroussi

7.3k total citations · 2 hit papers
100 papers, 4.4k citations indexed

About

G. Seroussi is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Networks and Communications. According to data from OpenAlex, G. Seroussi has authored 100 papers receiving a total of 4.4k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Artificial Intelligence, 29 papers in Computational Theory and Mathematics and 28 papers in Computer Networks and Communications. Recurrent topics in G. Seroussi's work include Algorithms and Data Compression (41 papers), Coding theory and cryptography (23 papers) and Cellular Automata and Applications (20 papers). G. Seroussi is often cited by papers focused on Algorithms and Data Compression (41 papers), Coding theory and cryptography (23 papers) and Cellular Automata and Applications (20 papers). G. Seroussi collaborates with scholars based in United States, Israel and Uruguay. G. Seroussi's co-authors include M.J. Weinberger, Guillermo Sapiro, Ian F. Blake, Nigel P. Smart, Erik Ordentlich, Ron M. Roth, Nader H. Bshouty, Sergio Verdú, Tsachy Weissman and A. Lempel and has published in prestigious journals such as Bioinformatics, Proceedings of the IEEE and IEEE Transactions on Information Theory.

In The Last Decade

G. Seroussi

90 papers receiving 3.9k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS

2000 1.1k citations M.J. Weinberger, G. Seroussi et al. IEEE Transactions on Image Processing profile →
Elliptic Curves in Cryptography

1999 981 citations G. Seroussi, Nigel P. Smart et al. profile →

Peers

G. Seroussi

CVPR

AI

IS

SP

CNC

Joe Kilian United States

Vincent Rijmen Belgium

James Cheng Hong Kong

Joan Daemen Netherlands

Mauro Barni Italy

John G. Cleary New Zealand

S. V. N. Vishwanathan United States

Alfred Menezes Canada

Ray C. C. Cheung Hong Kong

Rafail Ostrovsky United States

Joe Kilian United States

G. Seroussi

4.1k ×1.8

CVPR

2.4k ×1.1

AI

637 ×0.7

IS

518 ×0.6

SP

793 ×1.3

CNC

Citations per year, relative to G. Seroussi G. Seroussi (= 1×) peers Joe Kilian

Countries citing papers authored by G. Seroussi

Since Specialization

Citations

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

Fields of papers citing papers by G. Seroussi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of G. Seroussi

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Heß, Florian, G. Seroussi, & Nigel P. Smart. (2025). Selected Areas in Cryptography – SAC 2024. Lecture notes in computer science.

2.

Gutiérrez, Álvaro, et al.. (2024). The Lattice-Input Discrete-Time Poisson Channel. 3624–3629.

3.

Seroussi, G., et al.. (2024). Compression of Multichannel Signals With Irregular Sampling Rates and Data Gaps. IEEE Access. 12. 193195–193211.

4.

Ochoa, Idoia, et al.. (2022). Nanopore quality score resolution can be reduced with little effect on downstream analysis. Bioinformatics Advances. 2(1). vbac054–vbac054. 5 indexed citations

5.

Favaro, Federico, et al.. (2018). Wireless EEG System Achieving High Throughput and Reduced Energy Consumption Through Lossless and Near-Lossless Compression. IEEE Transactions on Biomedical Circuits and Systems. 12(1). 231–241. 25 indexed citations

6.

Seroussi, G., et al.. (2015). Space-efficient representation of truncated suffix trees, with applications to Markov order estimation. Theoretical Computer Science. 595. 34–45. 4 indexed citations

7.

Motta, Gaetano, Erik Ordentlich, Ignacio Ramírez, G. Seroussi, & M.J. Weinberger. (2010). The iDUDE Framework for Grayscale Image Denoising. IEEE Transactions on Image Processing. 20(1). 1–21. 46 indexed citations

8.

Jacquet, Philippe, G. Seroussi, & Wojciech Szpankowski. (2008). On the entropy of a hidden Markov process. Theoretical Computer Science. 395(2-3). 203–219. 39 indexed citations

9.

Seroussi, G., et al.. (2007). Type Classes of Tree Models. 886–890. 5 indexed citations

10.

Kuekes, Philip J., Warren Robinett, Ron M. Roth, et al.. (2006). Resistor-logic demultiplexers for nanoelectronics based on constant-weight codes. Nanotechnology. 17(4). 1052–1061. 27 indexed citations

11.

Sapiro, Guillermo, et al.. (2005). Is image steganography natural?. IEEE Transactions on Image Processing. 14(12). 2040–2050. 91 indexed citations

12.

Motta, Gaetano, Erik Ordentlich, Ignacio Ramírez, G. Seroussi, & M.J. Weinberger. (2005). The DUDE framework for continuous tone image denoising. III–345. 17 indexed citations

13.

Weissman, Tsachy, Erik Ordentlich, G. Seroussi, Sergio Verdú, & M.J. Weinberger. (2003). Inequalities for the L1 Deviation of the Empirical Distribution. The Netherlands Journal of Medicine. 69(7). 330–4. 74 indexed citations

14.

Weinberger, M.J., G. Seroussi, & Guillermo Sapiro. (2000). The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS. IEEE Transactions on Image Processing. 9(8). 1309–1324. 1119 indexed citations breakdown →

15.

Weinberger, M.J. & G. Seroussi. (1997). Sequential prediction and ranking in universal context modeling and data compression. IEEE Transactions on Information Theory. 43(5). 1697–1706. 21 indexed citations

16.

Κωνσταντινίδης, Κωνσταντίνος, et al.. (1993). Beam transformation techinques for ultrasonic medical imaging. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control. 40(6). 717–726. 19 indexed citations

17.

Seroussi, G. & Ron M. Roth. (1986). On MDS extensions of generalized Reed- Solomon codes. IEEE Transactions on Information Theory. 32(3). 349–354. 36 indexed citations

18.

Lempel, A., G. Seroussi, & S. Winograd. (1983). On the complexity of multiplication in finite fields. Theoretical Computer Science. 22(3). 285–296. 37 indexed citations

19.

Seroussi, G. & A. Lempel. (1983). On Symmetric Representations of Finite Fields. SIAM Journal on Algebraic and Discrete Methods. 4(1). 14–21. 8 indexed citations

20.

Seroussi, G. & Fai Ma. (1983). On the arithmetic complexity of matrix Kronecker powers. Information Processing Letters. 17(3). 145–148. 1 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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