Ryan N. Smith

1.6k total citations
71 papers, 1.1k citations indexed

About

Ryan N. Smith is a scholar working on Ocean Engineering, Oceanography and Artificial Intelligence. According to data from OpenAlex, Ryan N. Smith has authored 71 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Ocean Engineering, 27 papers in Oceanography and 17 papers in Artificial Intelligence. Recurrent topics in Ryan N. Smith's work include Underwater Vehicles and Communication Systems (44 papers), Maritime Navigation and Safety (17 papers) and Target Tracking and Data Fusion in Sensor Networks (15 papers). Ryan N. Smith is often cited by papers focused on Underwater Vehicles and Communication Systems (44 papers), Maritime Navigation and Safety (17 papers) and Target Tracking and Data Fusion in Sensor Networks (15 papers). Ryan N. Smith collaborates with scholars based in United States, Australia and Saudi Arabia. Ryan N. Smith's co-authors include Gaurav S. Sukhatme, Burton H. Jones, Wesam H. Alsabban, Van Thanh Huynh, David A. Caron, Yi Chao, Giacomo Marani, Felipé Gonzalez, Hyun‐Taek Choi and Fumin Zhang and has published in prestigious journals such as SHILAP Revista de lepidopterología, The International Journal of Robotics Research and Remote Sensing.

In The Last Decade

Ryan N. Smith

70 papers receiving 1.1k 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 N. Smith United States 17 655 309 265 255 204 71 1.1k
Brian Bingham United States 18 606 0.9× 204 0.7× 243 0.9× 281 1.1× 119 0.6× 42 1.0k
R. Stokey United States 20 968 1.5× 174 0.6× 330 1.2× 347 1.4× 91 0.4× 41 1.2k
Justin Manley United States 13 752 1.1× 205 0.7× 168 0.6× 183 0.7× 133 0.7× 47 1.1k
Toshihiro Maki Japan 19 859 1.3× 259 0.8× 254 1.0× 437 1.7× 81 0.4× 121 1.1k
Nuno Cruz Portugal 20 900 1.4× 188 0.6× 226 0.9× 312 1.2× 179 0.9× 124 1.2k
Ralf Bachmayer Canada 19 1.1k 1.6× 271 0.9× 345 1.3× 367 1.4× 399 2.0× 85 1.7k
Jnaneshwar Das United States 16 248 0.4× 197 0.6× 114 0.4× 163 0.6× 59 0.3× 48 1.1k
Riccardo Costanzi Italy 19 1.0k 1.5× 205 0.7× 280 1.1× 529 2.1× 145 0.7× 94 1.3k
B. Allen United States 14 728 1.1× 154 0.5× 218 0.8× 282 1.1× 76 0.4× 21 916
Alfredo Martins Portugal 18 592 0.9× 316 1.0× 71 0.3× 348 1.4× 85 0.4× 111 1.1k

Countries citing papers authored by Ryan N. Smith

Since Specialization
Citations

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

Fields of papers citing papers by Ryan N. Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ryan N. Smith

This figure shows the co-authorship network connecting the top 25 collaborators of Ryan N. Smith. A scholar is included among the top collaborators of Ryan N. Smith 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 N. Smith. Ryan N. Smith 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.
Osmanoğlu, Batuhan, et al.. (2022). Combining Remote and In-situ Sensing for Persistent Monitoring of Water Quality. OCEANS 2022 - Chennai. 6. 1–6.
2.
Bobadilla, Leonardo, et al.. (2021). Long-Term Autonomy for AUVs Operating Under Uncertainties in Dynamic Marine Environments. IEEE Robotics and Automation Letters. 6(4). 6313–6320. 12 indexed citations
3.
Bobadilla, Leonardo, et al.. (2021). Towards Energy-Aware Feedback Planning for Long-Range Autonomous Underwater Vehicles. Frontiers in Robotics and AI. 8. 621820–621820. 8 indexed citations
4.
Santana, Oliverio J., et al.. (2020). Neural Network Training for the Detection and Classification of Oceanic Mesoscale Eddies. Remote Sensing. 12(16). 2625–2625. 21 indexed citations
5.
Ferrari, Renata, David McKinnon, Hu He, et al.. (2016). Quantifying Multiscale Habitat Structural Complexity: A Cost-Effective Framework for Underwater 3D Modelling. Remote Sensing. 8(2). 113–113. 82 indexed citations
6.
Hsieh, M. Ani, et al.. (2015). Design and validation of a micro-AUV for 3-D sampling of coherent ocean features. 1–9. 1 indexed citations
7.
Das, Jnaneshwar, et al.. (2014). Predicting the speed of a Wave Glider autonomous surface vehicle from wave model data. QUT ePrints (Queensland University of Technology). 1 indexed citations
8.
Huynh, Van Thanh, Matthew Dunbabin, & Ryan N. Smith. (2014). Convergence-guaranteed time-varying RRT path planning for profiling floats in 4-dimensional flow. Deakin Research Online (Deakin University). 1–9. 2 indexed citations
9.
Alsabban, Wesam H., Felipé Gonzalez, Ryan N. Smith, & Gordon Wyeth. (2012). Wind-energy based path planning for electric unmanned aerial vehicles using Markov Decision Processes. QUT ePrints (Queensland University of Technology). 12 indexed citations
10.
He, Hu, Renata Ferrari, David McKinnon, et al.. (2012). Measuring reef complexity and rugosity from monocular video bathymetric reconstruction. QUT ePrints (Queensland University of Technology). 11 indexed citations
11.
Smith, Ryan N., et al.. (2012). A semi-local method for iterative depth-map refinement. 1. 758–763. 8 indexed citations
12.
Smith, Ryan N., Peter J. Prentis, Koen Langendoen, & Peter Corke. (2011). Pseudoseeds : investigating long-distance, ocean seed dispersal with wireless sensors. QUT ePrints (Queensland University of Technology). 1 indexed citations
13.
Smith, Ryan N. & Matthew Dunbabin. (2011). Controlled Drift: An Investigation into the Controllability of Underwater Vehicles with Minimal Actuation. QUT ePrints (Queensland University of Technology). 14 indexed citations
14.
Smith, Ryan N., Jnaneshwar Das, Hordur Heidarsson, et al.. (2010). USC CINAPS Builds bridges : observing and monitoring the southern california bight. QUT ePrints (Queensland University of Technology). 10 indexed citations
15.
Smith, Ryan N., Monique Chyba, S.K. Choi, & Giacomo Marani. (2009). Guidance and control for underactuated Autonomous Underwater Vehicles. QUT ePrints (Queensland University of Technology). 16(8). 37–41. 5 indexed citations
16.
Caron, David A., Beth Stauffer, Carl M. Öberg, et al.. (2009). Networked aquatic microbial observing systems: An overview. QUT ePrints (Queensland University of Technology). 2 indexed citations
17.
Smith, Ryan N., Beth Stauffer, Jnaneshwar Das, et al.. (2009). Design and implementation of sensor networks for the observation and research of harmful algal blooms in southern California coastal waters. QUT ePrints (Queensland University of Technology). 5–7. 2 indexed citations
18.
Chyba, Monique, et al.. (2008). Autonomous Underwater Vehicles: Development and Implementation of Time and Energy Efficient Trajectories. Ship Technology Research. 55(1). 36–48. 16 indexed citations
19.
Chyba, Monique, Thomas Haberkorn, Ryan N. Smith, & S.K. Choi. (2007). Design and implementation of time efficient trajectories for an underwater vehicle. Ocean Engineering. 9 indexed citations
20.
Chyba, Monique, Thomas Haberkorn, & Ryan N. Smith. (2005). Controllability and Optimal trajectories for Controlled Mechanical Systems: An Application to Underwater Vehicles. 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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