Andrea Di Blas

406 total citations
11 papers, 301 citations indexed

About

Andrea Di Blas is a scholar working on Artificial Intelligence, Computer Networks and Communications and Hardware and Architecture. According to data from OpenAlex, Andrea Di Blas has authored 11 papers receiving a total of 301 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Computer Networks and Communications and 4 papers in Hardware and Architecture. Recurrent topics in Andrea Di Blas's work include Parallel Computing and Optimization Techniques (4 papers), Algorithms and Data Compression (4 papers) and Neural Networks and Applications (2 papers). Andrea Di Blas is often cited by papers focused on Parallel Computing and Optimization Techniques (4 papers), Algorithms and Data Compression (4 papers) and Neural Networks and Applications (2 papers). Andrea Di Blas collaborates with scholars based in United States and United Kingdom. Andrea Di Blas's co-authors include Tim Kaldewey, Eric Sedlar, Nadathur Satish, Victor W. Lee, Changkyu Kim, Pradeep Dubey, Anthony D. Nguyen, Jatin Chhugani, Richard Hughey and Arun Jagota and has published in prestigious journals such as Proceedings of the VLDB Endowment, Cytometry Part A and Parallel Computing.

In The Last Decade

Andrea Di Blas

11 papers receiving 280 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Andrea Di Blas United States	6	229	101	88	84	79	11	301
Shengfei Shi China	9	138 0.6×	85 0.8×	55 0.6×	110 1.3×	43 0.5×	33	240
T. Johnson United States	11	304 1.3×	101 1.0×	75 0.9×	78 0.9×	102 1.3×	31	355
Michael L. Heytens United States	5	289 1.3×	59 0.6×	45 0.5×	98 1.2×	110 1.4×	11	341
Juncheng Yang United States	10	203 0.9×	111 1.1×	52 0.6×	117 1.4×	70 0.9×	27	325
Anil Shanbhag United States	10	289 1.3×	119 1.2×	92 1.0×	132 1.6×	134 1.7×	14	372
Manuel Rigger Singapore	9	153 0.7×	98 1.0×	84 1.0×	86 1.0×	47 0.6×	31	257
Vasiliki Kalavri Sweden	9	190 0.8×	108 1.1×	22 0.3×	136 1.6×	45 0.6×	26	275
Paul Rovner United States	9	160 0.7×	131 1.3×	61 0.7×	45 0.5×	38 0.5×	12	279
Yong Tang China	11	183 0.8×	118 1.2×	39 0.4×	152 1.8×	237 3.0×	36	359
Richard Sidle United States	9	480 2.1×	134 1.3×	93 1.1×	189 2.3×	178 2.3×	18	523

Countries citing papers authored by Andrea Di Blas

Since Specialization

Citations

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

Fields of papers citing papers by Andrea Di Blas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrea Di Blas. 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 Andrea Di Blas. The network helps show where Andrea Di Blas may publish in the future.

Co-authorship network of co-authors of Andrea Di Blas

This figure shows the co-authorship network connecting the top 25 collaborators of Andrea Di Blas. A scholar is included among the top collaborators of Andrea Di Blas 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 Andrea Di Blas. Andrea Di Blas 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:

11 of 11 papers shown

1.

Hill, Andrew W., Andrea Di Blas, & Richard Hughey. (2011). FPGA-based fine-grain parallel computing (abstract only). 283–283. 1 indexed citations

2.

Kaldewey, Tim, et al.. (2009). Parallel search on video cards. 9–9. 23 indexed citations

3.

Kim, Changkyu, Tim Kaldewey, Victor W. Lee, et al.. (2009). Sort vs. Hash revisited. Proceedings of the VLDB Endowment. 2(2). 1378–1389. 220 indexed citations

4.

Blas, Andrea Di & Tim Kaldewey. (2009). Data monster. IEEE Spectrum. 46(9). 46–51. 5 indexed citations

5.

Hughey, Richard & Andrea Di Blas. (2007). Finding the Next Computational Model: Experience with the UCSC Kestrel. Journal of Signal Processing Systems. 53(1-2). 171–186. 1 indexed citations

6.

Hughey, Richard & Andrea Di Blas. (2006). The UCSC Kestrel Application-Unspecific Processor. 1. 163–168. 4 indexed citations

7.

Ionescu‐Zanetti, Cristian, Lee‐Ping Wang, Dino Di Carlo, et al.. (2005). Alkaline hemolysis fragility is dependent on cell shape: Results from a morphology tracker. Cytometry Part A. 65A(2). 116–123. 11 indexed citations

8.

Blas, Andrea Di, Arun Jagota, & Richard Hughey. (2004). Optimizing neural networks on SIMD parallel computers. Parallel Computing. 31(1). 97–115. 8 indexed citations

9.

Blas, Andrea Di, Arun Jagota, & Richard Hughey. (2003). A Range-Compaction Heuristic for Graph Coloring. Journal of Heuristics. 9(6). 489–506. 3 indexed citations

10.

Blas, Andrea Di, Arun Jagota, & Richard Hughey. (2002). Energy function-based approaches to graph coloring. IEEE Transactions on Neural Networks. 13(1). 81–91. 20 indexed citations

11.

Blas, Andrea Di & Richard Hughey. (2002). Explicit SIMD programming for asynchronous applications. 258–267. 5 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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