Antonio Liotta

antonio liotta

Prof Antonio Liotta PhD MSc

Professor of Data Science and Intelligent Systems

Biography

Antonio Liotta (SMEEE’15) is Professor of Data Science and Intelligent Systems at Edinburgh Napier University, where is coordinating multi-disciplinary programs in Data Science and Artificial Intelligent across the university. Previously, he was Professor of Data Science and the founding director of the Data Science Research Centre, University of Derby, UK.
His team is at the forefront of influential research in data science and artificial intelligence, specifically in the context of Smart Cities, Internet of Things, and smart sensing. Antonio is a Fellow of the U.K. Higher Education Academy, and IEEE Senior Member. He is the Editor-in-Chief of the Springer Internet of Things book series; associate editor of the Journals JNSM, IJNM, JMM, and IF; and editorial board member of 6 more journals. He has 6 patents and over 350 publications to his credit, and is the author of the book "Networks for Pervasive Services: six ways to upgrade the Internet." He is renowned for his contributions to miniaturized machine learning, particularly in the context of the Internet of Things. He has led the international team that has recently made a breakthrough in artificial neural networks, using network science to accelerate the training process.

Esteem

Editorial Activity

  • Editor in Chief: Springer book series in Internet of Things

 

Visiting Positions

  • Visiting Professor at University of Cagliari, Italy
  • Visiting Professor at Shanghai Ocean University, China
  • Visiting Professor at Queensland University of Technology, Australia
  • Visiting Professor at University of Calabria, Italy
  • Visiting Professor at University of Derby, UK

 

Date


113 results

Improved Particle Swarm Optimization for Sea Surface Temperature Prediction

Journal Article
He, Q., Zha, C., Song, W., Hao, Z., Du, Y., Liotta, A., & Perra, C. (2020)
Improved Particle Swarm Optimization for Sea Surface Temperature Prediction. Energies, 13(6), https://doi.org/10.3390/en13061369
The Sea Surface Temperature (SST) is one of the key factors affecting ocean climate change. Hence, Sea Surface Temperature Prediction (SSTP) is of great significance to the st...

Artificial Neural Networks Training Acceleration Through Network Science Strategies

Conference Proceeding
Cavallaro, L., Bagdasar, O., De Meo, P., Fiumara, G., & Liotta, A. (2020)
Artificial Neural Networks Training Acceleration Through Network Science Strategies. In Numerical Computations: Theory and Algorithms. , (330-336). https://doi.org/10.1007/978-3-030-40616-5_27
Deep Learning opened artificial intelligence to an unprecedented number of new applications. A critical success factor is the ability to train deeper neural networks, striving...

An Online Learning Approach to a Multi-player N-armed Functional Bandit

Conference Proceeding
O’Neill, S., Bagdasar, O., & Liotta, A. (2020)
An Online Learning Approach to a Multi-player N-armed Functional Bandit. In Numerical Computations: Theory and Algorithms. , (438-445). https://doi.org/10.1007/978-3-030-40616-5_41
Congestion games possess the property of emitting at least one pure Nash equilibrium and have a rich history of practical use in transport modelling. In this paper we approach...

Enhancement of Underwater Images With Statistical Model of Background Light and Optimization of Transmission Map

Journal Article
Song, W., Wang, Y., Huang, D., Liotta, A., & Perra, C. (2020)
Enhancement of Underwater Images With Statistical Model of Background Light and Optimization of Transmission Map. IEEE Transactions on Broadcasting, 66(1), 153-169. https://doi.org/10.1109/tbc.2019.2960942
Underwater images often have severe quality degradation and distortion due to light absorption and scattering in the water medium. A hazy image formation model is widely used ...

Cloud-assisted Adaptive Stream Processing from Discriminative Representations

Conference Proceeding
Ndubuaku, M., Anjum, A., & Liotta, A. Cloud-assisted Adaptive Stream Processing from Discriminative Representations. https://doi.org/10.1109/smc.2019.8914227

)
Ndubuaku, M., Anjum, A., & Liotta, A. Cloud-assisted Adaptive Stream Processing from Discriminative Representations. https://doi.org/10.1109/smc.2019.8914227
As the streaming data generated by Internet of Things (IoT) ubiquitous sensors grow in massive scale, extracting interesting information (anomalies) in real-time becomes more ...

Unsupervised Anomaly Thresholding from Reconstruction Errors

Conference Proceeding
Ndubuaku, M. U., Anjum, A., & Liotta, A. (2019)
Unsupervised Anomaly Thresholding from Reconstruction Errors. In Unsupervised Anomaly Thresholding from Reconstruction Errors, (123-129). https://doi.org/10.1007/978-3-030-34914-1_12
Internet of Things (IoT) sensors generate massive streaming data which needs to be processed in real-time for many applications. Anomaly detection is one popular way to proces...

An AI approach to Collecting and Analyzing Human Interactions with Urban Environments

Journal Article
Ferrara, E., Fragale, L., Fortino, G., Song, W., Perra, C., di Mauro, M., & Liotta, A. (2019)
An AI approach to Collecting and Analyzing Human Interactions with Urban Environments. IEEE Access, 7, 141476-141486. https://doi.org/10.1109/access.2019.2943845
Thanks to advances in Internet of Things and crowd-sensing, it is possible to collect vast amounts of urban data, to better understand how citizens interact with cities and, i...

Statistical Assessment of IP Multimedia Subsystem in a Softwarized Environment: a Queueing Networks Approach

Journal Article
Di Mauro, M., & Liotta, A. (2019)
Statistical Assessment of IP Multimedia Subsystem in a Softwarized Environment: a Queueing Networks Approach. IEEE Transactions on Network and Service Management, 16(4), 1493-1506. https://doi.org/10.1109/tnsm.2019.2943776
The Next Generation 5G Networks can greatly benefit from the synergy between virtualization paradigms, such as the Network Function Virtualization (NFV), and service provision...

RSS Indoor Localization Based on a Single Access Point

Journal Article
Kokkinis, A., Kanaris, L., Liotta, A., & Stavrou, S. (2019)
RSS Indoor Localization Based on a Single Access Point. Sensors, 19(17), https://doi.org/10.3390/s19173711
This research work investigates how RSS information fusion from a single, multi-antenna access point (AP) can be used to perform device localization in indoor RSS based locali...

An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging

Journal Article
Wang, Y., Song, W., Fortino, G., Qi, L., Zhang, W., & Liotta, A. (2019)
An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging. IEEE Access, 7, 140233-140251. https://doi.org/10.1109/ACCESS.2019.2932130
Underwater images play a key role in ocean exploration, but often suffer from severe quality degradation due to light absorption and scattering in water medium. Although major...

Current Post Grad projects