Ryan Goldhahn

407 total citations
21 papers, 283 citations indexed

About

Ryan Goldhahn is a scholar working on Artificial Intelligence, Ocean Engineering and Oceanography. According to data from OpenAlex, Ryan Goldhahn has authored 21 papers receiving a total of 283 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 11 papers in Ocean Engineering and 9 papers in Oceanography. Recurrent topics in Ryan Goldhahn's work include Underwater Vehicles and Communication Systems (11 papers), Target Tracking and Data Fusion in Sensor Networks (10 papers) and Underwater Acoustics Research (9 papers). Ryan Goldhahn is often cited by papers focused on Underwater Vehicles and Communication Systems (11 papers), Target Tracking and Data Fusion in Sensor Networks (10 papers) and Underwater Acoustics Research (9 papers). Ryan Goldhahn collaborates with scholars based in United States, Italy and Belgium. Ryan Goldhahn's co-authors include Kevin D. LePage, Gabriele Ferri, Paolo Braca, Andrea Munafò, Jeffrey Krolik, Bhavya Kailkhura, Peter Willett, Vincenzo Matta, Stefano Maranò and Qunwei Li and has published in prestigious journals such as IEEE Transactions on Signal Processing, The Journal of the Acoustical Society of America and IEEE Sensors Journal.

In The Last Decade

Ryan Goldhahn

21 papers receiving 280 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ryan Goldhahn United States 9 171 130 114 87 71 21 283
Weihua Jiang China 10 180 1.1× 33 0.3× 127 1.1× 141 1.6× 45 0.6× 43 271
Robert Been Belgium 11 174 1.0× 68 0.5× 169 1.5× 70 0.8× 32 0.5× 30 306
К. Г. Кебкал Italy 12 406 2.4× 54 0.4× 190 1.7× 216 2.5× 126 1.8× 50 457
A.S. Gadre United States 8 259 1.5× 143 1.1× 95 0.8× 89 1.0× 54 0.8× 12 336
Zeyad A. H. Qasem China 14 189 1.1× 29 0.2× 82 0.7× 222 2.6× 32 0.5× 31 327
Benjamin Henson United Kingdom 11 264 1.5× 37 0.3× 127 1.1× 190 2.2× 35 0.5× 29 357
Srinivas Yerramalli United States 10 148 0.9× 37 0.3× 68 0.6× 209 2.4× 162 2.3× 21 323
Haining Shu United States 8 271 1.6× 60 0.5× 123 1.1× 282 3.2× 155 2.2× 9 389
Tianyi Jia China 9 135 0.8× 104 0.8× 75 0.7× 251 2.9× 44 0.6× 24 356
Zhongben Zhu China 11 176 1.0× 90 0.7× 83 0.7× 55 0.6× 32 0.5× 36 295

Countries citing papers authored by Ryan Goldhahn

Since Specialization
Citations

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

Fields of papers citing papers by Ryan Goldhahn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ryan Goldhahn

This figure shows the co-authorship network connecting the top 25 collaborators of Ryan Goldhahn. A scholar is included among the top collaborators of Ryan Goldhahn 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 Ryan Goldhahn. Ryan Goldhahn 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.
Bhardwaj, Kshitij, Zishen Wan, Arijit Raychowdhury, & Ryan Goldhahn. (2023). Real-Time Fully Unsupervised Domain Adaptation for Lane Detection in Autonomous Driving. 1–2. 2 indexed citations
2.
Li, Qunwei, Bhavya Kailkhura, Ryan Goldhahn, Priyadip Ray, & Pramod K. Varshney. (2022). Robust Decentralized Learning Using ADMM With Unreliable Agents. IEEE Transactions on Signal Processing. 70. 2743–2757. 3 indexed citations
3.
4.
Cheng, Hao, et al.. (2021). Mixture of Robust Experts (MoRE): A Flexible Defense Against Multiple Perturbations.. arXiv (Cornell University). 1 indexed citations
5.
Glatt, Ruben, et al.. (2021). Collaborative energy demand response with decentralized actor and centralized critic. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 333–337. 6 indexed citations
6.
Chen, Cheng, Bhavya Kailkhura, Ryan Goldhahn, & Yi Zhou. (2021). Certifiably-Robust Federated Adversarial Learning via Randomized Smoothing. arXiv (Cornell University). 173–179. 6 indexed citations
7.
Cadena, José, Priyadip Ray, Hao Chen, et al.. (2021). Stochastic Gradient-Based Distributed Bayesian Estimation in Cooperative Sensor Networks. IEEE Transactions on Signal Processing. 69. 1713–1724. 3 indexed citations
8.
Smith, Ralph C., et al.. (2019). Sequential optimal positioning of mobile sensors using mutual information. Statistical Analysis and Data Mining The ASA Data Science Journal. 12(6). 465–478. 7 indexed citations
9.
Munafò, Andrea, Gabriele Ferri, Kevin D. LePage, & Ryan Goldhahn. (2017). AUV active perception: Exploiting the water column. OCEANS 2017 - Aberdeen. 1–8. 14 indexed citations
10.
Braca, Paolo, Ryan Goldhahn, Gabriele Ferri, & Kevin D. LePage. (2015). Distributed Information Fusion in Multistatic Sensor Networks for Underwater Surveillance. IEEE Sensors Journal. 16(11). 4003–4014. 95 indexed citations
11.
Ferri, Gabriele, Andrea Munafò, Ryan Goldhahn, & Kevin D. LePage. (2015). Towards fully autonomous underwater vehicles in ASW scenarios: An adaptive, data driven AUV mission management layer. 1–9. 8 indexed citations
12.
Braca, Paolo, Ryan Goldhahn, Kevin D. LePage, et al.. (2014). Cognitive multistatic AUV networks. International Conference on Information Fusion. 1–7. 19 indexed citations
13.
Goldhahn, Ryan, Paolo Braca, Kevin D. LePage, et al.. (2014). Environmentally sensitive particle filter tracking in multistatic AUV networks with port-starboard ambiguity. 1458–1462. 7 indexed citations
14.
Ferri, Gabriele, Andrea Munafò, Ryan Goldhahn, & Kevin D. LePage. (2014). A non-myopic, receding horizon control strategy for an AUV to track an underwater target in a bistatic sonar scenario. 5352–5358. 24 indexed citations
15.
Munafò, Andrea, Gabriele Ferri, Ryan Goldhahn, et al.. (2014). Enhancing AUV localization using underwater acoustic sensor networks: Results in long baseline navigation from the COLLAB13 sea trial. 9. 1–7. 19 indexed citations
16.
Ferri, Gabriele, Andrea Munafò, Ryan Goldhahn, & Kevin D. LePage. (2014). Results from COLLAB13 sea trial on tracking underwater targets with AUVs in bistatic sonar scenarios. 1–9. 12 indexed citations
17.
Goldhahn, Ryan, et al.. (2011). A waveguide invariant adaptive matched filter for active sonar target depth classification. The Journal of the Acoustical Society of America. 129(4). 1813–1824. 13 indexed citations
18.
Goldhahn, Ryan, et al.. (2010). Waveguide invariant minimum variance scatterer depth classification for active sonar.. The Journal of the Acoustical Society of America. 127(3_Supplement). 2043–2043. 1 indexed citations
19.
Goldhahn, Ryan, et al.. (2008). Waveguide invariant broadband target detection and reverberation estimation. The Journal of the Acoustical Society of America. 124(5). 2841–2851. 24 indexed citations
20.
Goldhahn, Ryan, et al.. (2007). Waveguide Invariant Reverberation Mitigation for Active Sonar. 10 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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