Davide Mulfari

653 total citations
32 papers, 399 citations indexed

About

Davide Mulfari is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Davide Mulfari has authored 32 papers receiving a total of 399 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 9 papers in Artificial Intelligence and 7 papers in Computer Networks and Communications. Recurrent topics in Davide Mulfari's work include Speech Recognition and Synthesis (7 papers), Context-Aware Activity Recognition Systems (7 papers) and Voice and Speech Disorders (7 papers). Davide Mulfari is often cited by papers focused on Speech Recognition and Synthesis (7 papers), Context-Aware Activity Recognition Systems (7 papers) and Voice and Speech Disorders (7 papers). Davide Mulfari collaborates with scholars based in Italy, Russia and Norway. Davide Mulfari's co-authors include Massimo Villari, Antonio Celesti, Antonio Puliafito, Maria Fazio, Luca Fanucci, Gabriele Meoni, Lorenzo Carnevale, Maurizio Giacobbe, Alfonso Panarello and Antonino Galletta and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Applied Soft Computing.

In The Last Decade

Davide Mulfari

32 papers receiving 386 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Davide Mulfari Italy 11 161 131 84 70 42 32 399
Juan A. Nolazco‐Flores Mexico 13 161 1.0× 51 0.4× 91 1.1× 66 0.9× 14 0.3× 48 498
Wen‐Chen Hu United States 11 120 0.7× 65 0.5× 59 0.7× 27 0.4× 21 0.5× 58 365
Pawan Hegde India 5 112 0.7× 83 0.6× 66 0.8× 50 0.7× 9 0.2× 7 338
Malathi Devarajan India 13 169 1.0× 215 1.6× 170 2.0× 99 1.4× 14 0.3× 35 551
Erik Berglund Sweden 10 27 0.2× 53 0.4× 96 1.1× 83 1.2× 16 0.4× 41 346
Ala Saleh Alluhaidan Saudi Arabia 14 93 0.6× 80 0.6× 124 1.5× 87 1.2× 6 0.1× 67 509
Manghui Tu United States 9 156 1.0× 209 1.6× 52 0.6× 13 0.2× 11 0.3× 37 388
Franz J. Hauck Germany 14 423 2.6× 257 2.0× 104 1.2× 62 0.9× 6 0.1× 75 628
Ehsan Sheybani United States 8 47 0.3× 41 0.3× 60 0.7× 24 0.3× 7 0.2× 64 251
Raja Bose United States 12 224 1.4× 55 0.4× 46 0.5× 163 2.3× 3 0.1× 23 415

Countries citing papers authored by Davide Mulfari

Since Specialization
Citations

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

Fields of papers citing papers by Davide Mulfari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Davide Mulfari

This figure shows the co-authorship network connecting the top 25 collaborators of Davide Mulfari. A scholar is included among the top collaborators of Davide Mulfari 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 Davide Mulfari. Davide Mulfari 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.
Mulfari, Davide, et al.. (2024). Co-designing the integration of voice-based conversational AI and web augmentation to amplify web inclusivity. Scientific Reports. 14(1). 16162–16162. 4 indexed citations
2.
Mulfari, Davide, Lorenzo Carnevale, & Massimo Villari. (2024). Sequence-to-Sequence Models in Italian Atypical Speech Recognition. 1–6. 1 indexed citations
3.
Mulfari, Davide, Lorenzo Carnevale, & Massimo Villari. (2023). Toward a lightweight ASR solution for atypical speech on the edge. Future Generation Computer Systems. 149. 455–463. 4 indexed citations
4.
Mulfari, Davide, Lorenzo Carnevale, Antonino Galletta, & Massimo Villari. (2023). Edge Computing Solutions Supporting Voice Recognition Services for Speakers with Dysarthria. 231–236. 4 indexed citations
5.
Mulfari, Davide, et al.. (2022). Deep learning applications in telerehabilitation speech therapy scenarios. Computers in Biology and Medicine. 148. 105864–105864. 22 indexed citations
6.
Mulfari, Davide, Giuseppe Campobello, Giovanni Gugliandolo, et al.. (2022). Comparison of Noise Reduction Techniques for Dysarthric Speech Recognition. 1–6. 4 indexed citations
7.
Mulfari, Davide, Antonio Celesti, & Massimo Villari. (2022). Exploring AI-based Speaker Dependent Methods in Dysarthric Speech Recognition. 958–964. 3 indexed citations
8.
Celesti, Antonio, Davide Mulfari, Antonino Galletta, et al.. (2019). A study on container virtualization for guarantee quality of service in Cloud-of-Things. Future Generation Computer Systems. 99. 356–364. 25 indexed citations
9.
Bruneo, Dario, Salvatore Distefano, Maurizio Giacobbe, et al.. (2018). An IoT service ecosystem for Smart Cities: The #SmartME project. Internet of Things. 5. 12–33. 60 indexed citations
10.
Bruneo, Dario, Antonio Puliafito, Carlo Puliafito, et al.. (2018). Building a Smart City Service Platform in Messina with the #SmartME Project. CINECA IRIS Institutial research information system (University of Pisa). 6 indexed citations
11.
Mulfari, Davide. (2018). A TensorFlow-based Assistive Technology System for Users with Visual Impairments. 1–2. 11 indexed citations
12.
Mulfari, Davide, et al.. (2017). Embedded Systems and TensorFlow Frameworks as Assistive Technology Solutions. Studies in health technology and informatics. 242. 396–400. 1 indexed citations
13.
Mulfari, Davide, et al.. (2017). USING TENSORFLOW TO DESIGN ASSISTIVE TECHNOLOGIES FOR PEOPLE WITH VISUAL IMPAIRMENTS. CINECA IRIS Institutial research information system (University of Pisa). 110–116. 1 indexed citations
14.
Mulfari, Davide, et al.. (2017). Building TensorFlow Applications in Smart City Scenarios. 1–5. 11 indexed citations
15.
Mulfari, Davide, Antonio Celesti, Maria Fazio, Massimo Villari, & Antonio Puliafito. (2016). Using Google Cloud Vision in assistive technology scenarios. 214–219. 37 indexed citations
16.
Mulfari, Davide, Antonio Celesti, Maria Fazio, Massimo Villari, & Antonio Puliafito. (2015). Embedded systems for supporting computer accessibility. Studies in health technology and informatics. 217. 378–85. 1 indexed citations
17.
Mulfari, Davide, Antonio Celesti, Massimo Villari, & Antonio Puliafito. (2014). Providing Assistive Technology Applications as a Service Through Cloud Computing. Assistive Technology. 27(1). 44–51. 6 indexed citations
18.
Mulfari, Davide, Antonio Celesti, Maria Fazio, Massimo Villari, & Antonio Puliafito. (2014). Using embedded systems to spread assistive technology on multiple devices in smart environments. 12. 5–11. 2 indexed citations
19.
Mulfari, Davide, Antonio Celesti, & Massimo Villari. (2014). A computer system architecture providing a user-friendly man machine interface for accessing assistive technology in cloud computing. Journal of Systems and Software. 100. 129–138. 10 indexed citations
20.
Celesti, Antonio, Maria Fazio, Massimo Villari, Antonio Puliafito, & Davide Mulfari. (2013). Remote and deep attestations to mitigate threats in Cloud Mash-Up services. 15. 1–6. 2 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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