Francesco Piccialli is currently Assistant Professor (tenure track) of Computer Science at the Department of Mathematics and Applications “R. Caccioppoli” (DMA), University of Naples Federico II (UNINA), Italy. In 2018 he took the Italian Scientific Habilitation for Associate Professorship. He received a Laurea Degree (BSc+MSc) in Computer Science and the Ph.D. in Computational and Computer sciences at the Unviersity of Naples Federico II.

He is the founder and Scientific director of the M.O.D.A.L. research group that is engaged in cutting-edge on novel methodologies, architectures and applications in the Artificial Intelligence, Machine and Deep Learning fields also focusing on their emerging application domains. He is also research fellow at C.I.N.I. (National Interuniversity Consortium for Informatics) from 2013.

He has been involved in research and development projects in the research areas of Artificial Intelligence, Data Science and Internet of Things. He is author of many scientific papers (130+) in international conferences and top-ranking journals (IEEE, ACM, Springer, Elsevier, Wiley, Nature). Currently he serves as Associate Editor of many prestigious, international and well-recognized journals.

My research interests fall within the Data Science, Artificial Intelligence and the Internet of Things research area. In particular, the main research themes are:

• Modelling of Deep Learning frameworks and applications
• Algorithms and Applications in Machine Learning
• Data Prediction in IoT environments
• Internet of Things architecture and applications

My research activities - often carried out in collaboration with national and international universities, research centres and companies - establish theoretical and practical approaches and aim to provide tools for the development of intelligent environments that improve the quality of life of people who live in such environments.

My research is also oriented to solving practical problems by emphasizing the transfer of research results to the community and making data, algorithms and software / hardware tools freely available.

Coordination of (funded) Research Projects

• Principal Investigator - 4I: mixed reality, machine learning, gamification and educational for Industry, M.I.S.E., Programma Operativo Nazionale Imprese e competitività 2014-2020 FESR, Prog n. F/190130/01/X44 - 2021 - 2023
• Principal Investigator - C.E.T.R.A - Cultural Equipment with Transmedial Recommendation Analytics - POR FESR CAMPANIA 2014/2020 - O.S. 1.1- 2017-2020
• Principal Investigator - CUP-i-ONE – CUP in un Click, POR FESR CAMPANIA 2014/2020 - O.S. 1.1”- 2017-2020
• Principal Investigator - A.M.I. - Advanced Modalities of Interactions, Prog. n. F/050398/03/X32, HORIZON2020, PON I&C 2014-2020 - 2016-2018
• Principal Investigator - Touristic Platform Systems, POR Campania 2018-2020, Obiettivo Operativo 1.1 e 1.4, 2017-2019

Participation to (funded) Research Projects

• Research Unit Member - BIOCHIP - Intelligent biosensors based on chimeric proteins, F.R.A - funding for university research, 2021-2023
• Research Activities Manager - C.H.I.S. - Cultural Heritage Information System, PON03PE_0099_1, 2014-2017
• Research Unit Member - S.N.E.C.S. - Social Network delle Entità dei Centri Storici, PON03PE_00163_1, 2014-2017
• Research Unit Member - Muse@Home - Smart Service and Technologies for Virtual Tours in Museums and Archeological Sites Enjoyable@Home,PAC02L200221, 2014-2016
• Research Unit Member - MITO – Multimedia Information for Territorial Objects, PAC01_00119, 2014-2015

Selected Publications

• 2022 - I. Ahmed, G. Jeon, F. Piccialli, From Artificial Intelligence to eXplainable Artificial Intelligence in Industry 4.0: A survey on What, How, and Where, IEEE Transactions on Industrial Informatics, DOI: 10.1109/TII.2022.3146552
• 2022 - A. Pennacchio, F. Giampaolo, F. Piccialli, S. Cuomo, E. Notomista, M. Spinelli, A. Amoresano, A. Piscitelli, P. Giardina, A machine learning-enhanced biosensor for mercury detection based on an hydrophobin chimera, Biosensors and Bioelectronics, Vol. 196, DOI: https://doi.org/10.1016/j.bios.2021.113696
• 2021 - E. Prezioso, S. Izzo, F. Giampaolo, F. Piccialli, G. Dell'Aversana Orabona, R. Cuocolo, V. Abbate, L. Ugga, L. Califano, Predictive Medicine for Salivary gland tumours identification through Deep Learning, IEEE Journal of Biomedical and Health Informatics, DOI: 10.1109/JBHI.2021.3120178
• 2021 - F Piccialli, V Di Cola, F Giampaolo, S Cuomo, The Role of Artificial Intelligence in Fighting the COVID-19 Pandemic, Information System Frontiers, DOI: https://doi.org/10.1007/s10796-021-10131-x
• 2021 - F Piccialli, F Giampaolo, E Prezioso, D Camacho, G Acampora, Artificial intelligence and healthcare: Forecasting of medical bookings through multi-source time-series fusion, Information Fusion, Vol. 74, pp. 1-16
• 2021 - F Piccialli, V Di Somma, F Giampaolo, S Cuomo, G Fortino, A survey on deep learning in medicine: Why, how and when?, Information Fusion, Vol. 66, pp. 111-137
• 2021 - F Piccialli, F Giampaolo, E Prezioso, D Crisci, S Cuomo, Predictive Analytics for Smart Parking: A Deep Learning Approach in Forecasting of IoT Data, ACM Transactions on Internet Technology, Vol. 21 (3), pp. 1-21
• 2021 - F Piccialli, F Giampaolo, A Salvi, S Cuomo, A Robust Ensemble Technique in Forecasting Workload of Local Healthcare Departments, Neurocomputing, Vol. 444, pp. 69-78
• 2020 - F Piccialli, S Cuomo, D Crisci, E Prezioso, G Mei, A deep learning approach for facility patient attendance prediction based on medical booking data, Scientific Reports, Nature 10 (1), 1-11
• 2020 - Z Lv, L Qiao, Q Wang, F Piccialli, Advanced machine-learning methods for brain-computer interfacing, IEEE/ACM Transactions on Computational Biology and Bioinformatics, DOI: 10.1109/TCBB.2020.3010014
• 2020 - F Piccialli, F Giampaolo, G Casolla, VS Di Cola, K Li, A Deep Learning approach for Path Prediction in a Location-based IoT system, Pervasive and Mobile Computing, Vol. 66, 101210
• 2020 - F Ahmed, S Ahmad, L Kenli, L Keqin, F Piccialli, Deep end-to-end learning for price prediction of second-hand items, Knowledge and Information Systems, 1-28
• 2019 - F Piccialli, G Casolla, S Cuomo, F Giampaolo, VS Di Cola, Decision making in IoT environment through unsupervised learning, IEEE Intelligent Systems, Vol. 35 (1), pp. 27-35
• 2019 - G Casolla, S Cuomo, VS Di Cola, F Piccialli, Exploring unsupervised learning techniques for the Internet of Things, IEEE Transactions on Industrial Informatics, Vol. 16 (4), pp. 2621-2628
• 2018 - F Piccialli, P Benedusi, F Amato, S-InTime: A social cloud analytical service oriented system, Future Generation Computer Systems, Vol. 80, pp. 229-241
• 2017 - S Cuomo, P De Michele, F Piccialli, A Galletti, JE Jung, IoT-based collaborative reputation system for associating visitors and artworks in a cultural scenario, Expert Systems with Applications, Vol.79, 101-111
• 2017 - A Chianese, F Marulli, F Piccialli, P Benedusi, JE Jung, An associative engines based approach supporting collaborative analytics in the internet of cultural things, Future generation computer systems, Vol. 66, pp.187-198

Links

• Google Scholar
• ResearchGate
• DBLP
• Scopus

Associate Editor and Editorial Board Member of the following top-ranking journals.

• IEEE Transactions on Artificial Intelligence (TAI)
• Scientific Reports, Nature
• IEEE Transactions on Industrial Informatics (TII)
• IEEE Internet of Things
• Future Generation Computer Systems - Elsevier
• Information Fusion - Elsevier
• Neural Computing And Applications - Springer (Associate Editor for Europe)
• Computer and Electrical Engineering - Elsevier
• IEEE Access
• Personal and Ubiquitous Computing - Springer
• Journal of Internet Technology - Ministry of Education – Taiwan

Technical Program Committee member (selected) of the following top-ranking international conferences.

• ACM MULTIMEDIA 2022 - [CORE: A++ - GGS Rating: A++]
• ISWC 2022 - [CORE: A - GGS Rating: A+]
• CIKM 2022 - [CORE: A - GGS Rating: A+]
• RTSS 2022 - [CORE: A++ - GGS Rating: A+]
• ECML-PKDD 2022 - [CORE: A - GGS Rating: A]
• ICWS 2022 - [CORE: A - GGS Rating: A]
• ICDCS 2022 - [CORE: A - GGS Rating: A]
• CCGRID 2022 - [CORE: A - GGS Rating: A]
• AIED 2022 - [CORE: A - GGS Rating: B]
• AISTATS 2020 - [CORE: A - GGS Rating: A+]
• ECML-PKDD 2020 - [CORE: A - GGS Rating: A]
• ESWC 2020 - [CORE: A - GGS Rating: A-]
• WISE 2018,2021 - [CORE: B - GGS Rating: B]
• KES 2018,2021 - [CORE: B]
• MoMM 2018,2019,2020,2021 - [CORE: B]
• TRUSTCOM 2021 - [CORE: B]
• TPDL 2018, 2020 - [CORE: B]
• DEXA 2018 - [CORE: B]
• VSVM 2018 [CORE: B]
• UIC 2018 - [CORE: B]
• ADMA 2018 - [CORE: B - GGS Rating B-]
• MUM 2018 - [CORE: B - GGS Rating B-]

IEEE and ACM Committees

• Franceco Piccialli is member of IEEE
• Member of IEEE Systems, Man, and Cybernetics Society Committee
• Franceco Piccialli is also member of ACM

Reviewer for international Journals

Since 2012, Francesco Piccialli serves and has served as Reviewer of scientific and technical papers for several top ranked Journals in the field of Artificial Intelligence, Data Science, Internet of Things. Examples are: Computer Communications Journal (Elsevier), Journal of Internet Technology (Taiwan Academic Network, Ministry of Education, TW), Journal of Network and Computer Applications (Elsevier), Computer Networks Journal (Elsevier), Future Generation Computer Systems (Elsevier), Computation and Concurrency: Practice and Experience (Wiley), Information Fusion (Elsevier), IEEE Journal on Selected Areas in Communications, IEEE Transactions on Industrial Informatics, IEEE Access, IEEE Transactions on Systems, Man and Cybernetics: Systems, Neural Computing and Applications (Springer), Big Data Research journal (Elsevier), Journal of Computing and Cultural Heritage (ACM), ACM Transactions on Internet Technology (ACM), Multimedia Tools and Applications (Springer.

Courses

• Algoritms and Applications for Data Science - Master Degree in Mathematics
• Programming Laboratory - Bachelor Degree in Mathematics
• Fundaments of Computer Science - Bachelor Degree in Computer Science Engineering

-- Institutional Web Page Link --

Scientific Tutor of the following Ph.D. Students

• Vincenzo Schiano Di Cola (2018-2022)
• Fabio Giampaolo (2020-2024)
• Edoardo Prezioso (2021-2024)
• Diletta Chiaro (2021-2024)
• Pian Qi (2021-2024)
• Stefano Izzo (2022-2025)

Scientific Tutor of the following Research Fellow

• Stefano Izzo (2021-2022)
• Federico Gatta (2021-2023)

Master Thesis

I supervised and/or co-supervised the following MS thesis in Computer Science, Applied Mathematics and Mathematical Engineering.

• Giampaolo Casolla
• Fabio Giampaolo
• Edoardo Prezioso
• Danilo Crisci
• Andrea di Palma
• Stefano Izzo
• Federico Gatta
• Giuseppe De Giovanni
• Martina Savoia
• Daniela Annunziata
• Francesco Fato