Aurelio Uncini

6.3k total citations · 1 hit paper
213 papers, 4.0k citations indexed

About

Aurelio Uncini is a scholar working on Signal Processing, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Aurelio Uncini has authored 213 papers receiving a total of 4.0k indexed citations (citations by other indexed papers that have themselves been cited), including 130 papers in Signal Processing, 89 papers in Artificial Intelligence and 71 papers in Computational Mechanics. Recurrent topics in Aurelio Uncini's work include Advanced Adaptive Filtering Techniques (67 papers), Speech and Audio Processing (63 papers) and Neural Networks and Applications (63 papers). Aurelio Uncini is often cited by papers focused on Advanced Adaptive Filtering Techniques (67 papers), Speech and Audio Processing (63 papers) and Neural Networks and Applications (63 papers). Aurelio Uncini collaborates with scholars based in Italy, Spain and United States. Aurelio Uncini's co-authors include Danilo Comminiello, Simone Scardapane, Michele Scarpiniti, Francesco Piazza, Raffaele Parisi, Amir Hussain, Indro Spinelli, Michele Marchesi, Massimo Panella and N. Benvenuto and has published in prestigious journals such as Neurology, IEEE Transactions on Signal Processing and Expert Systems with Applications.

In The Last Decade

Aurelio Uncini

200 papers receiving 3.9k citations

Hit Papers

Group sparse regularization for deep neural networks 2017 2026 2020 2023 2017 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Aurelio Uncini Italy 35 1.7k 1.6k 1.2k 1.0k 583 213 4.0k
Weifeng Liu China 33 1.4k 0.8× 1.1k 0.7× 1.2k 1.0× 1.7k 1.7× 324 0.6× 252 4.7k
Jiashu Zhang China 39 934 0.5× 2.1k 1.3× 1.6k 1.3× 1.9k 1.8× 410 0.7× 248 4.9k
Wenwu Wang United Kingdom 33 1.4k 0.8× 3.0k 1.9× 754 0.6× 1.5k 1.5× 167 0.3× 376 5.0k
Weifeng Liu China 15 844 0.5× 1.1k 0.7× 1.1k 0.9× 569 0.6× 315 0.5× 118 2.4k
Qianli Ma China 26 1.4k 0.8× 496 0.3× 482 0.4× 757 0.7× 274 0.5× 101 3.2k
M. Omair Ahmad Canada 35 630 0.4× 1.5k 1.0× 531 0.4× 2.6k 2.6× 242 0.4× 407 4.8k
Jiuwen Cao China 38 2.2k 1.3× 741 0.5× 305 0.3× 926 0.9× 506 0.9× 220 4.9k
Zhiguo Shi China 36 1.1k 0.6× 2.2k 1.4× 495 0.4× 653 0.6× 462 0.8× 349 6.5k
Jonathon A. Chambers United Kingdom 41 3.1k 1.8× 1.4k 0.9× 640 0.5× 1.3k 1.2× 1.1k 1.9× 211 6.8k
Nojun Kwak South Korea 29 1.9k 1.1× 522 0.3× 367 0.3× 2.3k 2.2× 279 0.5× 151 4.4k

Countries citing papers authored by Aurelio Uncini

Since Specialization
Citations

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

Fields of papers citing papers by Aurelio Uncini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aurelio Uncini

This figure shows the co-authorship network connecting the top 25 collaborators of Aurelio Uncini. A scholar is included among the top collaborators of Aurelio Uncini 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 Aurelio Uncini. Aurelio Uncini 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
2.
Comminiello, Danilo, Eleonora Grassucci, Danilo P. Mandic, & Aurelio Uncini. (2024). Demystifying the Hypercomplex: Inductive biases in hypercomplex deep learning. IEEE Signal Processing Magazine. 41(3). 59–71. 4 indexed citations
3.
Scarpiniti, Michele, et al.. (2024). Spline Adaptive Exponential Functional Link Filter for Nonlinear Acoustic Echo Cancellation. 216–220. 1 indexed citations
4.
Uncini, Aurelio, et al.. (2024). Hierarchical Hypercomplex Network for Multimodal Emotion Recognition. IRIS Research product catalog (Sapienza University of Rome). 1–6. 4 indexed citations
5.
Scardapane, Simone, et al.. (2023). Continual learning with invertible generative models. Neural Networks. 164. 606–616. 2 indexed citations
6.
Comminiello, Danilo, et al.. (2022). A New Class of Efficient Adaptive Filters for Online Nonlinear Modeling. IEEE Transactions on Systems Man and Cybernetics Systems. 53(3). 1384–1396. 10 indexed citations
7.
Scardapane, Simone, et al.. (2021). Structured ensembles. An approach to reduce the memory footprint of ensemble methods. IRIS Research product catalog (Sapienza University of Rome). 4 indexed citations
8.
Grassucci, Eleonora, Danilo Comminiello, & Aurelio Uncini. (2021). A quaternion-valued variational autoencoder. IRIS Research product catalog (Sapienza University of Rome). 17 indexed citations
9.
Scardapane, Simone, Steven Van Vaerenbergh, Amir Hussain, & Aurelio Uncini. (2020). Complex-valued neural networks with nonparametric activation functions. IRIS Research product catalog (Sapienza University of Rome). 53 indexed citations
10.
Scardapane, Simone, et al.. (2019). Kafnets: Kernel-based non-parametric activation functions for neural networks. IRIS Research product catalog (Sapienza University of Rome). 48 indexed citations
11.
Scardapane, Simone, Michele Scarpiniti, Danilo Comminiello, & Aurelio Uncini. (2016). Diffusion spline adaptive filtering. IRIS Research product catalog (Sapienza University of Rome). 1498–1502. 25 indexed citations
12.
Scardapane, Simone, et al.. (2016). Distributed semi-supervised support vector machines. Neural Networks. 80. 43–52. 39 indexed citations
13.
Patel, Vinal, Danilo Comminiello, Michele Scarpiniti, Nithin V. George, & Aurelio Uncini. (2016). Design of hybrid nonlinear spline adaptive filters for active noise control. IRIS Research product catalog (Sapienza University of Rome). assp 33. 3420–3425. 9 indexed citations
14.
Bianchi, Filippo Maria, Simone Scardapane, Aurelio Uncini, Antonello Rizzi, & Alireza Sadeghian. (2015). Prediction of telephone calls load using Echo State Network with exogenous variables. Neural Networks. 71. 204–213. 59 indexed citations
15.
Romoli, Laura, Stefania Cecchi, Danilo Comminiello, Francesco Piazza, & Aurelio Uncini. (2014). Novel decorrelation approach for an advanced multichannel acoustic echo cancellation system. IRIS Research product catalog (Sapienza University of Rome). 651–655. 5 indexed citations
16.
Uncini, Aurelio. (2014). Fundamentals of Adaptive Signal Processing. Signals and communication technology. 64 indexed citations
17.
Comminiello, Danilo, Michele Scarpiniti, Raffaele Parisi, & Aurelio Uncini. (2013). Intelligent acoustic interfaces for immersive audio. Journal of the Audio Engineering Society. 8 indexed citations
18.
Uncini, Aurelio, et al.. (2013). Polar Measurements of Harmonic and Multitone Distortion of Direct Radiating and Horn Loaded Transducers. Journal of the Audio Engineering Society. 1 indexed citations
19.
Comminiello, Danilo, Simone Scardapane, Michele Scarpiniti, & Aurelio Uncini. (2013). User-driven quality enhancement for audio signal processing. Journal of the Audio Engineering Society. 608–615. 4 indexed citations
20.
Piazza, Francesco, et al.. (1999). Multilayer feedforward networks with adaptive spline activation function. IEEE Transactions on Neural Networks. 10(3). 672–683. 80 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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