Lance Kaplan

7.5k total citations
239 papers, 4.8k citations indexed

About

Lance Kaplan is a scholar working on Artificial Intelligence, Computer Networks and Communications and Electrical and Electronic Engineering. According to data from OpenAlex, Lance Kaplan has authored 239 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 113 papers in Artificial Intelligence, 64 papers in Computer Networks and Communications and 41 papers in Electrical and Electronic Engineering. Recurrent topics in Lance Kaplan's work include Distributed Sensor Networks and Detection Algorithms (42 papers), Indoor and Outdoor Localization Technologies (38 papers) and Target Tracking and Data Fusion in Sensor Networks (38 papers). Lance Kaplan is often cited by papers focused on Distributed Sensor Networks and Detection Algorithms (42 papers), Indoor and Outdoor Localization Technologies (38 papers) and Target Tracking and Data Fusion in Sensor Networks (38 papers). Lance Kaplan collaborates with scholars based in United States, United Kingdom and Italy. Lance Kaplan's co-authors include Tarek Abdelzaher, Dong Wang, C.‐C. Jay Kuo, Hieu Le, James H. McClellan, Mani Srivastava, Yeo-Sun Yoon, Jiawei Han, Erik Blasch and Chun Yang and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Information Theory.

In The Last Decade

Lance Kaplan

228 papers receiving 4.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lance Kaplan United States 37 1.9k 1.1k 1.0k 951 699 239 4.8k
Dong Wang United States 33 1.7k 0.9× 635 0.6× 1.5k 1.5× 372 0.4× 622 0.9× 295 4.1k
Suresh Venkatasubramanian United States 27 3.8k 2.0× 736 0.6× 473 0.5× 462 0.5× 595 0.9× 114 6.0k
John C. Duchi United States 31 5.5k 2.9× 863 0.8× 257 0.2× 758 0.8× 2.0k 2.9× 80 8.8k
Sewoong Oh United States 24 1.4k 0.7× 435 0.4× 785 0.8× 437 0.5× 531 0.8× 112 3.4k
Dit‐Yan Yeung Hong Kong 44 4.1k 2.2× 740 0.7× 597 0.6× 395 0.4× 5.4k 7.7× 152 9.5k
Jianliang Xu Hong Kong 44 2.3k 1.2× 3.0k 2.6× 311 0.3× 696 0.7× 679 1.0× 353 6.0k
Jie Yin Australia 28 1.7k 0.9× 788 0.7× 96 0.1× 713 0.7× 603 0.9× 98 3.6k
S. S. Iyengar United States 31 1.5k 0.8× 1.8k 1.6× 152 0.1× 1.1k 1.2× 1.1k 1.5× 217 5.1k
Shie Mannor Israel 42 3.9k 2.1× 1.6k 1.4× 98 0.1× 1.7k 1.7× 1.4k 1.9× 252 8.7k
Fan Li China 27 1.8k 1.0× 628 0.6× 137 0.1× 841 0.9× 1.5k 2.1× 203 4.2k

Countries citing papers authored by Lance Kaplan

Since Specialization
Citations

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

Fields of papers citing papers by Lance Kaplan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lance Kaplan

This figure shows the co-authorship network connecting the top 25 collaborators of Lance Kaplan. A scholar is included among the top collaborators of Lance Kaplan 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 Lance Kaplan. Lance Kaplan 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.
Kaplan, Lance, et al.. (2025). Beyond Binary Opinions: A Deep Reinforcement Learning-Based Approach to Uncertainty-Aware Competitive Influence Maximization. IEEE Transactions on Network Science and Engineering. 13. 2219–2235. 1 indexed citations
2.
Şensoy, Murat, et al.. (2024). Risk-aware classification via uncertainty quantification. Expert Systems with Applications. 265. 125906–125906. 1 indexed citations
3.
Jeong, Dong Hyun, Jin-Hee Cho, Feng Chen, et al.. (2022). Interactive Web-Based Visual Analysis on Network Traffic Data. Information. 14(1). 16–16. 2 indexed citations
4.
Shao, Huajie, Shuochao Yao, Lü Su, et al.. (2020). Truth Discovery With Multi-Modal Data in Social Sensing. IEEE Transactions on Computers. 70(9). 1325–1337. 15 indexed citations
5.
Saebi, Mandana, Giovanni Luca Ciampaglia, Lance Kaplan, & Nitesh V. Chawla. (2020). HONEM: Learning Embedding for Higher Order Networks. Big Data. 8(4). 255–269. 12 indexed citations
6.
Shi, Yu, Huan Gui, Qi Zhu, Lance Kaplan, & Jiawei Han. (2018). AspEm: Embedding Learning by Aspects in Heterogeneous Information Networks. Society for Industrial and Applied Mathematics eBooks. 2018. 144–152. 62 indexed citations
7.
Zhang, Chao, Quan Yuan, Honglei Zhuang, et al.. (2018). GeoBurst+. ACM Transactions on Intelligent Systems and Technology. 9(3). 1–24. 33 indexed citations
8.
Jiang, Wenjun, Chenglin Miao, Lü Su, et al.. (2017). Towards Quality Aware Information Integration in Distributed Sensing Systems. IEEE Transactions on Parallel and Distributed Systems. 29(1). 198–211. 10 indexed citations
9.
Jøsang, Audun & Lance Kaplan. (2016). Principles of subjective networks. International Conference on Information Fusion. 1292–1299. 6 indexed citations
10.
Kaplan, Lance, et al.. (2015). Towards subjective networks: Extending conditional reasoning in subjective logic. International Conference on Information Fusion. 319–326. 3 indexed citations
11.
Kaplan, Lance, Murat Şensoy, & Geeth de Mel. (2014). Trust estimation and fusion of uncertain information by exploiting consistency. ECS Journal of Solid State Science and Technology (The Electrochemical Society). 1–8. 15 indexed citations
12.
George, Jemin, et al.. (2014). Multi-shooter localization using finite point process. International Conference on Information Fusion. 1–7. 9 indexed citations
13.
Şensoy, Murat, et al.. (2013). TRIBE: Trust revision for information based on evidence. International Conference on Information Fusion. 914–921. 7 indexed citations
14.
Kaplan, Lance, Murat Şensoy, Yuqing Tang, et al.. (2013). Reasoning under uncertainty: Variations of subjective logic deduction. ECS Journal of Solid State Science and Technology (The Electrochemical Society). 1910–1917. 8 indexed citations
15.
George, Jemin & Lance Kaplan. (2013). Shooter Localization using a Wireless Sensor Network of Soldier-Worn Gunfire Detection Systems.. 8. 15–32. 8 indexed citations
16.
Kaplan, Lance, Supriyo Chakraborty, & Chatschik Bisdikian. (2012). Subjective logic with uncertain partial observations. International Conference on Information Fusion. 565–572. 6 indexed citations
17.
Chakraborty, Supriyo, et al.. (2012). Balancing value and risk in information sharing through obfuscation. International Conference on Information Fusion. 1615–1622. 5 indexed citations
18.
Bisdikian, Chatschik, et al.. (2011). QoI-based resource allocation for multi-target tracking in energy constrained sensor networks. International Conference on Information Fusion. 1–8. 4 indexed citations
19.
Kaplan, Lance, et al.. (2006). Energy-Aware Node Selection In A Distributed Sensor Network. Defense Technical Information Center (DTIC).
20.
Kaplan, Lance, et al.. (2001). <title>Bearings-only target localization for an acoustical unattended ground sensor network</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 4393. 40–51. 22 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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