G.A. Williamson

2.9k total citations · 1 hit paper
79 papers, 2.2k citations indexed

About

G.A. Williamson is a scholar working on Computational Mechanics, Control and Systems Engineering and Signal Processing. According to data from OpenAlex, G.A. Williamson has authored 79 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Computational Mechanics, 26 papers in Control and Systems Engineering and 22 papers in Signal Processing. Recurrent topics in G.A. Williamson's work include Advanced Adaptive Filtering Techniques (38 papers), Control Systems and Identification (19 papers) and Image and Signal Denoising Methods (15 papers). G.A. Williamson is often cited by papers focused on Advanced Adaptive Filtering Techniques (38 papers), Control Systems and Identification (19 papers) and Image and Signal Denoising Methods (15 papers). G.A. Williamson collaborates with scholars based in United States, Australia and Türkiye. G.A. Williamson's co-authors include Ali Emadi, Claudio Rivetta, Alireza Khaligh, Karen A. Griffin, A. Bidani, Rodger Loutzenhiser, C. Rivetta, Rıfat Hacıoğlu, Amir Rahimi and Babak Fahimi and has published in prestigious journals such as IEEE Transactions on Automatic Control, Automatica and Hypertension.

In The Last Decade

G.A. Williamson

70 papers receiving 2.1k citations

Hit Papers

Constant Power Loads and Negative Impedance Instability i... 2006 2026 2012 2019 2006 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
G.A. Williamson United States 21 1.2k 1.1k 359 265 205 79 2.2k
Ling Fu China 18 754 0.6× 623 0.6× 29 0.1× 37 0.1× 48 0.2× 49 1.9k
Xun Zhang China 18 561 0.5× 63 0.1× 287 0.8× 230 0.9× 22 0.1× 143 1.6k
Yossi Chait United States 21 192 0.2× 1.1k 1.0× 22 0.1× 89 0.3× 26 0.1× 91 1.7k
Shahzad Ahmad Qureshi Pakistan 17 720 0.6× 60 0.1× 31 0.1× 84 0.3× 10 0.0× 67 1.5k
José Ignacio Suárez Spain 17 226 0.2× 234 0.2× 36 0.1× 27 0.1× 26 0.1× 49 1.3k
Jiann-Der Lee Taiwan 24 89 0.1× 44 0.0× 206 0.6× 35 0.1× 14 0.1× 191 2.0k
Tadashi Kitamura Japan 25 86 0.1× 103 0.1× 354 1.0× 20 0.1× 18 0.1× 219 2.8k
Jianguo Li China 16 169 0.1× 32 0.0× 126 0.4× 12 0.0× 23 0.1× 50 2.6k
Xiaoguang Hu China 20 469 0.4× 378 0.3× 19 0.1× 12 0.0× 25 0.1× 175 1.6k
Rong Chen China 20 224 0.2× 129 0.1× 87 0.2× 10 0.0× 66 0.3× 72 1.3k

Countries citing papers authored by G.A. Williamson

Since Specialization
Citations

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

Fields of papers citing papers by G.A. Williamson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by G.A. Williamson. 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 G.A. Williamson. The network helps show where G.A. Williamson may publish in the future.

Co-authorship network of co-authors of G.A. Williamson

This figure shows the co-authorship network connecting the top 25 collaborators of G.A. Williamson. A scholar is included among the top collaborators of G.A. Williamson 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 G.A. Williamson. G.A. Williamson 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.
Polichnowski, Aaron J., et al.. (2021). Autonomic and cholinergic mechanisms mediating cardiovascular and temperature effects of donepezil in conscious mice. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology. 320(6). R871–R884. 2 indexed citations
2.
Williamson, G.A., et al.. (2021). On Estimating Nonlinear Frequency Modulated Radar Signals in Low SNR Environments. IEEE Transactions on Aerospace and Electronic Systems. 57(3). 1793–1802. 8 indexed citations
3.
Polichnowski, Aaron J., Karen A. Griffin, Rongpei Lan, et al.. (2020). Pathophysiology of unilateral ischemia-reperfusion injury: importance of renal counterbalance and implications for the AKI-CKD transition. American Journal of Physiology-Renal Physiology. 318(5). F1086–F1099. 35 indexed citations
4.
Polichnowski, Aaron J., et al.. (2020). Autoregulatory Efficiency Assessment in Kidneys Using Deep Learning. PubMed. 2020. 1165–1169.
5.
Picken, Maria M., et al.. (2016). Progression of Chronic Kidney Disease After Acute Kidney Injury. Hypertension. 68(4). 921–928. 15 indexed citations
6.
Williamson, G.A., et al.. (2014). Novel Radar Signal Models Using Nonlinear Frequency Modulation. INFM-OAR (INFN Catania). 1024–1028. 8 indexed citations
7.
Williamson, G.A., Rodger Loutzenhiser, Xuemei Wang, Karen A. Griffin, & A. Bidani. (2008). Systolic and mean blood pressures and afferent arteriolar myogenic response dynamics: a modeling approach. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology. 295(5). R1502–R1511. 17 indexed citations
8.
Griffin, Karen A., et al.. (2007). Dynamic blood pressure load and nephropathy in the ZSF1 (fa/facp) model of type 2 diabetes. American Journal of Physiology-Renal Physiology. 293(5). F1605–F1613. 45 indexed citations
9.
Loutzenhiser, Rodger, Karen A. Griffin, G.A. Williamson, & A. Bidani. (2006). Renal autoregulation: new perspectives regarding the protective and regulatory roles of the underlying mechanisms. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology. 290(5). R1153–R1167. 205 indexed citations
10.
Bidani, A., Maria M. Picken, Rıfat Hacıoğlu, G.A. Williamson, & Karen A. Griffin. (2006). Spontaneously reduced blood pressure load in the rat streptozotocin-induced diabetes model: potential pathogenetic relevance. American Journal of Physiology-Renal Physiology. 292(2). F647–F654. 35 indexed citations
11.
Hacıoğlu, Rıfat, G.A. Williamson, Isam Abu‐Amarah, Karen A. Griffin, & A. Bidani. (2006). Characterization of Dynamics in Renal Autoregulation Using Volterra Models. IEEE Transactions on Biomedical Engineering. 53(11). 2166–2176. 3 indexed citations
14.
Griffin, Karen A., Rıfat Hacıoğlu, Isam Abu‐Amarah, et al.. (2004). Effects of calcium channel blockers on “dynamic” and “steady-state step” renal autoregulation. American Journal of Physiology-Renal Physiology. 286(6). F1136–F1143. 43 indexed citations
15.
Rivetta, C. & G.A. Williamson. (2004). Large-signal analysis of a DC-DC buck power converter operating with constant power load. 732–737. 31 indexed citations
16.
Bidani, A., Rıfat Hacıoğlu, Isam Abu‐Amarah, et al.. (2003). “Step” vs. “dynamic” autoregulation: implications for susceptibility to hypertensive injury. American Journal of Physiology-Renal Physiology. 285(1). F113–F120. 62 indexed citations
17.
Williamson, G.A.. (2002). Implementations of adaptive IIR filters with lowest complexity. 3. 1772–1775. 1 indexed citations
18.
Fu, Yifeng & G.A. Williamson. (2002). Convergence of adaptive algorithms with order statistic based gradient estimates. 2. 397–400. 1 indexed citations
19.
Hacıoğlu, Rıfat & G.A. Williamson. (2001). Reduced Complexity Volterra Models for Nonlinear System Identification. EURASIP Journal on Advances in Signal Processing. 2001(4). 257–265. 42 indexed citations
20.
Fu, Minyue, Soura Dasgupta, & G.A. Williamson. (1996). Algorithms for Optimal Multirate Filter Bank Design. 1. 399–402. 4 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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