Machine Learning and Deep Learning in Smart Industry


Bianchini Monica Bianchini

Monica Bianchini

University of Siena, Italy

Andreini Paolo Andreini

Paolo Andreini

University of Siena, Italy

Bonechi Simone Bonechi

Simone Bonechi

University of Siena, Italy

Fort Ada Fort

Ada Fort

University of Siena, Italy

Mugnaini Marco Mugnaini

Marco Mugnaini

University of Siena, Italy


Recently, machine learning and deep learning have had a huge impact in the field of Smart Industry, as they allow to automatize and optimize processes, predict their outcomes, and detect patterns and anomalies in data. This can lead to increased efficiency, reduced costs, and improved decision-making. Indeed, many companies are changing their processes in order to fit the smart industry paradigm. Specifically, deep learning applied to computer vision and natural language processing can be used to analyze images, videos, and text data from multimedia sources to gain insights and make predictions in complex environments. AI techniques in the pharmaceutical industry have had a disrupting impact, covering the whole production chain, from drug discovery to automatized packaging techniques. AI-enabled smart manufacturing can predict when maintenance is needed, analyzing equipment sensor data, detecting manufacturing anomalies, optimizing supply chain; analyzing data on customer demand, inventory levels, and shipping routes.


Due to the wide range of applications of AI-based approaches to Smart Industry, the scope of this session comprehends, but it is not limited to:

  • Predictive maintenance
  • Anomaly detection
  • Supply chain optimization
  • Computer vision and Natural Language Processing in Industry 4.0
  • Machine learning for business improvement and quality control
  • Autonomus veichle in logistics
  • Intelligent energy management
  • Predictive analytics in healthcare
  • Analysis of biological and biomedical data for biomarker assessment and precision medicine


Monica Bianchini received her master’s degree cum laude in Applied Mathematics in 1989 and her PhD in Computer Science and Control Systems in 1995 from the University of Florence, Italy. She is currently Associate Professor at the Department of Information Engineering and Mathematics of the University of Siena. Her main research interests are in the field of machine learning, with emphasis on neural networks for structured data and deep learning, approximation theory, bioinformatics, and image processing. M. Bianchini has authored more than one hundred and thirty papers (http://scholar.google.it/citations?user=cKB0wzwAAA) and has been the editor of books and special issues on international journals in her research field. She has served/serves as Associate Editor for IEEE Transactions on Neural Networks, Neurocomputing, Int. J. of Knowledge-Based and Intelligent Engineering Systems, Int. J. of Computers in Healthcare, Frontiers in Genetics, and was editor of numerous books and special issues in international journals on neural networks, structural pattern recognition and bioinformatics.

Paolo Andreini is a postdoc at the University of Siena (Italy), has a degree in computer science and a PhD in Computer Engineering and Computer Science. His PhD thesis focused on proposing new generative models that can be trained from very limited datasets and can thus be used in the absence of large sets of data. He has worked on a variety of topics in the field of image generation with applications to biomedical images (chest xr, retinal imaging, agar plates, oocytes, etc…) and natural images (text segmentation in natural and cluttered scenes). His interest in image generation encompasses both theory and practice. He has also worked on many other research topics with specific applications in medicine, bioinformatics and computer vision. He is the author of 29 publications in international journals and conferences. He is theorganiser and chairman of a special session at the ESANN 2022 conference entitled “Deep Semantic segmentation models in computer vision”.

Simone Bonechi graduated in Computer Science at the Department of Information Engineering and Mathematical Sciences of the University of Siena (2014) where he then obtained his PhD. In 2018 he spent a period as a visiting PhD at the University of Copenhagen (2018). After two years of PostDoc, first at the University of Tuscia, and then at the University of Pisa, he is now a researcher at the Department of Social, Political and Cognitive Sciences of the University of Siena. His research activity is focused on Deep Learning and Artificial Intelligence, with particular reference to computer vision, image processing and image generation. He is the author of over 25 publications in international journals and conference proceedings. He also carries out editorial activities as Associated Editor for the journal Neurocomputing and he is Guest Editor for the Special Issue “Mathematical Modelling and Machine Learning Methods for Bioinformatics and Data Science Applications II” for the journal Mathematics.

Ada Fort received the Laurea degree in electronic engineering and the Ph.D. degree in nondestructive testing from the University of Florence, Florence, Italy, in 1989 and 1992, respectively. She is currently a Full Professor with the Department of Information Engineering, University of Siena, Siena, Italy. Her current research interests include the development of measurement systems based on advanced sensors and distributed measurement systems, with special reference to chemical sensors and bio-sensors, Internet of Things and wireless sensor networks.

Marco Mugnaini (Senior Member, IEEE) received the Laurea degree (cum laude) in electronics engineering with a major in nonlinear automatic controls and the Ph.D. degree in reliability availability and logistics from the University of Florence, Florence, Italy, in 1999 and 2003, respectively. He was a Faculty Member and a Professor with the Electrical and Electronics Technology Department, Higher Colleges of Technology, Abu Dhabi, UAE, from 2012 to 2013. He is currently the Manager of the Electronics Training Laboratory and an Associate Professor with the University of Siena, Siena, Italy. Dr. Mugnaini was awarded as the IEEE I&M Distinguished Lecturer from 2017 to 2020. His current research interests include the development of measurement systems based on advanced sensors and distributed measurement systems, , Internet of Things and wireless sensor networks.