David Vengerov

742 total citations
31 papers, 476 citations indexed

About

David Vengerov is a scholar working on Computer Networks and Communications, Artificial Intelligence and Hardware and Architecture. According to data from OpenAlex, David Vengerov has authored 31 papers receiving a total of 476 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Networks and Communications, 15 papers in Artificial Intelligence and 7 papers in Hardware and Architecture. Recurrent topics in David Vengerov's work include Reinforcement Learning in Robotics (12 papers), Parallel Computing and Optimization Techniques (7 papers) and Cloud Computing and Resource Management (5 papers). David Vengerov is often cited by papers focused on Reinforcement Learning in Robotics (12 papers), Parallel Computing and Optimization Techniques (7 papers) and Cloud Computing and Resource Management (5 papers). David Vengerov collaborates with scholars based in United States, Canada and United Kingdom. David Vengerov's co-authors include H.R. Berenji, Nicholas Bambos, Mohamed Zaït, Alexandra Fedorova, Vana Kalogeraki, Jeremy Singer, Reza Langari, Vivien Quéma, Justin Funston and M. Jamshidi and has published in prestigious journals such as Technometrics, Psychological Science and IEEE Transactions on Fuzzy Systems.

In The Last Decade

David Vengerov

31 papers receiving 432 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
David Vengerov United States	14	256	200	133	67	53	31	476
Nashat Mansour Lebanon	16	181 0.7×	143 0.7×	218 1.6×	39 0.6×	41 0.8×	51	676
Angelo Furfaro Italy	13	215 0.8×	117 0.6×	160 1.2×	58 0.9×	73 1.4×	85	589
Marin Golub Croatia	13	98 0.4×	201 1.0×	69 0.5×	31 0.5×	29 0.5×	46	403
Nathan Fulton United States	4	531 2.1×	164 0.8×	269 2.0×	86 1.3×	53 1.0×	8	721
Ludger Fiege Germany	16	644 2.5×	165 0.8×	199 1.5×	70 1.0×	20 0.4×	39	815
Panagiotis Katsaros Greece	13	210 0.8×	195 1.0×	196 1.5×	30 0.4×	30 0.6×	65	461
Boqin Feng China	11	111 0.4×	199 1.0×	163 1.2×	34 0.5×	21 0.4×	82	463
Man‐Tak Shing United States	13	162 0.6×	164 0.8×	155 1.2×	58 0.9×	49 0.9×	79	504
Muzammil Shahbaz United Kingdom	9	165 0.6×	201 1.0×	422 3.2×	44 0.7×	27 0.5×	15	839

Countries citing papers authored by David Vengerov

Since Specialization

Citations

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

Fields of papers citing papers by David Vengerov

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Vengerov

This figure shows the co-authorship network connecting the top 25 collaborators of David Vengerov. A scholar is included among the top collaborators of David Vengerov 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 David Vengerov. David Vengerov 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

Sanders, Lauren, Navid Zebarjadi, Holly C. Beale, et al.. (2022). Machine learning multi-omics analysis reveals cancer driver dysregulation in pan-cancer cell lines compared to primary tumors. Communications Biology. 5(1). 1367–1367. 6 indexed citations

Funston, Justin, et al.. (2018). Placement of Virtual Containers on NUMA systems: A Practical and Comprehensive Model. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 281–294. 4 indexed citations

Singer, Jeremy, et al.. (2015). The judgment of forseti: economic utility for dynamic heap sizing of multiple runtimes. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 143–156. 7 indexed citations

Vengerov, David, et al.. (2015). Join size estimation subject to filter conditions. Proceedings of the VLDB Endowment. 8(12). 1530–1541. 67 indexed citations

Singer, Jeremy, et al.. (2015). The judgment of forseti: economic utility for dynamic heap sizing of multiple runtimes. ACM SIGPLAN Notices. 50(11). 143–156. 3 indexed citations

Vengerov, David, et al.. (2011). FACT. 1–10. 20 indexed citations

Vengerov, David, et al.. (2009). Adaptive optimization of the Sun Java™ real-time system garbage collector. Psychological Science. 16(8). 579–84. 2 indexed citations

Vengerov, David, et al.. (2009). Adaptive data-aware utility-based scheduling in resource-constrained systems. Journal of Parallel and Distributed Computing. 70(9). 871–879. 11 indexed citations

Vengerov, David. (2009). Modeling, analysis and throughput optimization of a generational garbage collector. 1–9. 16 indexed citations

10.

Vengerov, David. (2008). A reinforcement learning framework for utility-based scheduling in resource-constrained systems. Future Generation Computer Systems. 25(7). 728–736. 25 indexed citations

11.

Vengerov, David. (2007). A reinforcement learning framework for online data migration in hierarchical storage systems. The Journal of Supercomputing. 43(1). 1–19. 16 indexed citations

12.

Vengerov, David, et al.. (2007). Constrained Multivariate Extrapolation Models With Application to Computer Cache Rates. Technometrics. 49(2). 129–137. 5 indexed citations

13.

Vengerov, David. (2006). Dynamic tuning of online data migration policies in hierarchical storage systems using reinforcement learning. 3 indexed citations

14.

Vengerov, David, Nicholas Bambos, & H.R. Berenji. (2005). A fuzzy reinforcement learning approach to power control in wireless transmitters. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 35(4). 768–778. 36 indexed citations

15.

Berenji, H.R. & David Vengerov. (2005). On convergence of fuzzy reinforcement learning. 3. 618–621. 6 indexed citations

16.

Vengerov, David, et al.. (2005). A Reinforcement Learning Framework for Dynamic Resource Allocation: First Results.. 339–340. 23 indexed citations

17.

Berenji, H.R., et al.. (2005). Using gated experts in fault diagnosis and prognosis. 1. 463–467. 4 indexed citations

18.

Berenji, H.R., et al.. (2004). Inductive learning for fault diagnosis. 31. 726–731. 18 indexed citations

19.

Berenji, H.R. & David Vengerov. (2002). Advantages of cooperation between reinforcement learning agents in difficult stochastic problems. 2. 871–876. 25 indexed citations

20.

Berenji, H.R. & David Vengerov. (1999). Cooperation and coordination between fuzzy reinforcement learning agents in continuous state partially observable Markov decision processes. 621–627 vol.2. 20 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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