Todd K. Leen

5.7k total citations · 2 hit papers
64 papers, 3.9k citations indexed

About

Todd K. Leen is a scholar working on Artificial Intelligence, Signal Processing and Cognitive Neuroscience. According to data from OpenAlex, Todd K. Leen has authored 64 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Artificial Intelligence, 14 papers in Signal Processing and 10 papers in Cognitive Neuroscience. Recurrent topics in Todd K. Leen's work include Neural Networks and Applications (22 papers), Neural dynamics and brain function (8 papers) and Image and Signal Denoising Methods (8 papers). Todd K. Leen is often cited by papers focused on Neural Networks and Applications (22 papers), Neural dynamics and brain function (8 papers) and Image and Signal Denoising Methods (8 papers). Todd K. Leen collaborates with scholars based in United States, United Kingdom and China. Todd K. Leen's co-authors include Volker Tresp, Thomas G. Dietterich, Nandakishore Kambhatla, David S. Touretzky, G. Tesauro, Gin McCollum, Zhengdong Lu, Michael E. Labhard, Ethan E. Gorenstein and Margaret E. Morris and has published in prestigious journals such as Journal of Applied Physics, IEEE Transactions on Pattern Analysis and Machine Intelligence and Water Resources Research.

In The Last Decade

Todd K. Leen

61 papers receiving 3.8k citations

Hit Papers

Proceedings of the 13th International Conference on Neura... 1995 2026 2005 2015 2000 1995 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Todd K. Leen United States 20 1.6k 1.0k 370 312 261 64 3.9k
P. A. Estévez Chile 28 1.4k 0.8× 923 0.9× 394 1.1× 295 0.9× 358 1.4× 131 3.5k
Zoubin Ghahramani United Kingdom 20 2.1k 1.3× 994 1.0× 301 0.8× 469 1.5× 190 0.7× 45 4.6k
Tom Dietterich United States 11 2.1k 1.3× 890 0.9× 238 0.6× 179 0.6× 146 0.6× 20 3.3k
Pavel Pudil Czechia 15 1.5k 0.9× 1.3k 1.2× 416 1.1× 282 0.9× 134 0.5× 63 3.5k
豊 松尾 3 1.7k 1.0× 1.5k 1.5× 296 0.8× 136 0.4× 277 1.1× 5 3.6k
S.R. Gunn United Kingdom 16 1.3k 0.8× 1.1k 1.1× 362 1.0× 159 0.5× 332 1.3× 41 4.4k
Barbara Hammer Germany 35 3.0k 1.8× 1.5k 1.5× 489 1.3× 310 1.0× 292 1.1× 347 4.9k
Ke Chen China 31 1.7k 1.0× 904 0.9× 556 1.5× 276 0.9× 184 0.7× 229 3.5k
Senén Barro Spain 30 1.6k 1.0× 444 0.4× 361 1.0× 337 1.1× 299 1.1× 137 4.4k
Amos Storkey United Kingdom 28 1.6k 1.0× 1.0k 1.0× 277 0.7× 737 2.4× 184 0.7× 106 4.0k

Countries citing papers authored by Todd K. Leen

Since Specialization
Citations

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

Fields of papers citing papers by Todd K. Leen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Todd K. Leen. 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 Todd K. Leen. The network helps show where Todd K. Leen may publish in the future.

Co-authorship network of co-authors of Todd K. Leen

This figure shows the co-authorship network connecting the top 25 collaborators of Todd K. Leen. A scholar is included among the top collaborators of Todd K. Leen 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 Todd K. Leen. Todd K. Leen 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.
Leen, Todd K.. (2018). Optimal stochastic search and adaptive momentum. OHSU Digital Commons. 6. 477–484. 4 indexed citations
2.
Akçakaya, Murat, et al.. (2017). Asymptotic analysis of objectives based on fisher information in active learning. arXiv (Cornell University). 18(1). 1123–1163. 7 indexed citations
3.
Lu, Zhengdong, Todd K. Leen, & Jeffrey Kaye. (2011). Kernels for Longitudinal Data with Variable Sequence Length and Sampling Intervals. Neural Computation. 23(9). 2390–2420. 2 indexed citations
4.
Kain, Alexander & Todd K. Leen. (2010). Compression of line spectral frequency parameters using the asynchronous interpolation model.. SSW. 49–54. 1 indexed citations
5.
Austin, Daniel, Todd K. Leen, Thomas Hayes, et al.. (2010). Model-based inference of cognitive processes from unobtrusive gait velocity measurements. PubMed. 2010. 5230–5233. 3 indexed citations
6.
Morris, Margaret E., et al.. (2010). Mobile Therapy: Case Study Evaluations of a Cell Phone Application for Emotional Self-Awareness. Journal of Medical Internet Research. 12(2). e10–e10. 257 indexed citations
7.
Roberts, Patrick D. & Todd K. Leen. (2010). Anti-Hebbian Spike-Timing-Dependent Plasticity and Adaptive Sensory Processing. Frontiers in Computational Neuroscience. 4. 156–156. 26 indexed citations
8.
Pavel, Misha, Holly Jimison, Tamara Hayes, et al.. (2010). Optimizing Medication Reminders Using a Decision-Theoretic Framework. Studies in health technology and informatics. 160(Pt 2). 791–5. 6 indexed citations
9.
Lu, Zhengdong, Jeffrey Kaye, & Todd K. Leen. (2008). Hierarchical Fisher Kernels for Longitudinal Data. Neural Information Processing Systems. 21. 1961–1968. 1 indexed citations
10.
Kazmierczak, Steven C., Todd K. Leen, Deniz Erdoğmuş, & Miguel Á. Carreira-Perpiñán. (2007). Reduction of multi-dimensional laboratory data to a two-dimensional plot: a novel technique for the identification of laboratory error. Clinical Chemistry and Laboratory Medicine (CCLM). 45(6). 749–52. 2 indexed citations
11.
Merwe, Rudolph van der, Todd K. Leen, Zhengdong Lu, Sergey Frolov, & António M. Baptista. (2007). Fast neural network surrogates for very high dimensional physics-based models in computational oceanography. Neural Networks. 20(4). 462–478. 45 indexed citations
12.
Baptista, António M., et al.. (2006). Assimilating in-situ Measurements into a Reduced-Dimensionality Model of an Estuary- Plume System.. AGU Fall Meeting Abstracts. 2006. 2 indexed citations
13.
Lu, Zhengdong & Todd K. Leen. (2004). Semi-supervised Learning with Penalized Probabilistic Clustering. Neural Information Processing Systems. 17. 849–856. 68 indexed citations
14.
Leen, Todd K., et al.. (2004). Random walks for spike-timing-dependent plasticity. Physical Review E. 70(2). 21916–21916. 5 indexed citations
15.
Leen, Todd K., et al.. (2003). Parameterized Novelty Detectors for Environmental Sensor Monitoring. Neural Information Processing Systems. 16. 619–626. 3 indexed citations
16.
Roberts, Patrick D., et al.. (2003). Stability of negative-image equilibria in spike-timing-dependent plasticity. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 68(2). 21923–21923. 16 indexed citations
17.
Saad, David, Chris Bishop, Léon Bottou, et al.. (1999). On-Line Learning in Neural Networks. Cambridge University Press eBooks. 97 indexed citations
18.
Leen, Todd K., et al.. (1997). Two Approaches to Optimal Annealing. Neural Information Processing Systems. 10. 301–307. 3 indexed citations
19.
Orr, Genevieve & Todd K. Leen. (1996). Using Curvature Information for Fast Stochastic Search. Neural Information Processing Systems. 9. 606–612. 21 indexed citations
20.
McCollum, Gin & Todd K. Leen. (1989). Form and Exploration of Mechanical Stability Limits in Erect Stance. Journal of Motor Behavior. 21(3). 225–244. 175 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026