Francesco Piccialli is currently Associate Professor of Computer Science and Artificial Intelligence 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 head and co-founder 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 Machine Learning, Artificial Intelligence and Internet of Things research area. In particular, the main research themes are:

• Modelling of Deep Learning architectures and applications
• Algorithms and Applications in Machine Learning
• Data Prediction and Analysis 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 - G.A.N.D.A.L.F - Gan Approaches for Non-iiD Aiding Learning in Federations, PRIN 2022, 2023 - 2025
• Research Unit Coordinator - D.I.R.E.C.T.I.O.N.S. - Deep learning aIded foReshock deteCTIOn Of iNduced mainShocks, PRIN PNRR 2022, 2023 - 2025
• Principal Investigator - C.L.A.I.M. - Artificial Intelligence for Competences and Learning, Programma Erasmus+, KA220-VET, Unione Europea, 2023 - 2025
• Work Package Leader @UNINA - Future Artificial Intelligence Research – FAIR, PNRR Recovery Plan, Partenariato Esteso sull'Intelligenza Artificiale, 2023 - 2026
• Work Package Leader @UNINA - CN1 - National Centre for HPC, Big Data and Quantum Computing, Spoke 9 - Digital Society & Smart Cities, PNRR Recovery Plan, 2022 - 2025
• Project Leader and Applicant - Deep-Learning-aided GPC-IR fingerprinting of complex polyolefin mixtures (DL-PO), DUTCH POLYMER INSTITUTE, 2023 - 2026
• Research Unit Coordinator - ELIXIR x NextGenerationIT, PNRR - Rafforzamento e creazione di IR nell’ambito del Piano Nazionale di Ripresa e Resilienza (PNRR) 2022 - 2025
• 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

Recent Selected Publications

• 2023 - F Giampaolo, F Gatta, E Prezioso, S Cuomo, M Zhou, G Fortino, F Piccialli, ENCODE-Ensemble neural combination for optimal dimensionality encoding in time-series forecasting, Information Fusion, DOI: https://doi.org/10.1016/j.inffus.2023.101918
• 2023 - V Rodriguez-Fernandez, D Montalvo-Garcia, F Piccialli, G J Nalepa, D Camacho, DeepVATS: Deep Visual Analytics for Time Series, Knowledge-Based Systems, DOI: https://doi.org/10.1016/j.knosys.2023.110793
• 2023 - P Qi, D Chiaro, F Piccialli, FL-FD: Federated learning-based fall detection with multimodal data fusion, Information Fusion, DOI: https://doi.org/10.1016/j.inffus.2023.101890
• 2023 - F Giampaolo, S Izzo, E Prezioso, F Piccialli, Investigating Random Variations of the Forward-Forward Algorithm for Training Neural Networks, 2023 International Joint Conference on Neural Networks (IJCNN), DOI: 10.1109/IJCNN54540.2023.10191727
• 2023 - P Qi, D Chiaro, F Giampaolo, F Piccialli, A blockchain-based secure Internet of medical things framework for stress detection, Information Sciences, DOI: https://doi.org/10.1016/j.ins.2023.01.123
• 2023 - R Gipiškis, D Chiaro, M Preziosi, E Prezioso, F Piccialli, The Impact of Adversarial Attacks on Interpretable Semantic Segmentation in Cyber–Physical Systems, IEEE Systems Journal, DOI: 10.1109/JSYST.2023.3281079
• 2022 - S Cuomo, F Gatta, F Giampaolo, C Iorio, F Piccialli, An unsupervised learning framework for market-neutral portfolio, DOI: 10.1016/j.eswa.2021.116308
• 2022 - F Gatta, F Giampaolo, E Prezioso, G Mei, S Cuomo, F Piccialli, Neural networks generative models for time series, DOI: 10.1016/j.jksuci.2022.07.010
• 2022 - S Cuomo, VS Di Cola, F Giampaolo, G Rozza, M Raissi, F Piccialli, Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next, DOI: 10.1007/s10915-022-01939-z
• 2022 - S Cuomo, F Giampaolo, S Izzo, C Nitsch, F Piccialli, C Trombetti, A physics-informed learning approach to Bernoulli-type free boundary problems, DOI: 10.1016/j.camwa.2022.10.003
• 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 - 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

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 (2016-2023)
• IEEE Access
• Personal and Ubiquitous Computing - Springer
• Journal of Internet Technology - Ministry of Education – Taiwan
• Communications on Applied Mathematics and Computation - Springer

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

• ICDCS 2023 - [CORE: A - GGS Rating: A]
• UAI 2023 - [CORE: A - GGS Rating: A]
• ECIR 2023 - [CORE: A - GGS Rating: A-]
• ESWC 2023,2020 - [CORE: A - GGS Rating: A-]
• ICWS 2023,2022 - [CORE: A - GGS Rating: A]
• ACM MULTIMEDIA 2023,2022 (AREA CHAIRS) - [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 2023,2022,2020 - [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]
• WISE 2021,2018 - [CORE: B - GGS Rating: B]
• KES 2021,2018 - [CORE: B]
• MoMM 2021,2020,2019,2018 - [CORE: B]
• AISTATS 2020 - [CORE: A - GGS Rating: A+]
• 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 Artificial Intelligence - Master Degree in Mathematics
• Programming Laboratory - Bachelor Degree in Mathematics
• Computational Intelligence - Master Degree in Data Science
• Fundaments of Computer Science - Bachelor Degree in Computer Science Engineering (2017-2023)

-- 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)
• Martina Savoia (2023-2026)
• Daniela Annunziata (2023-2026)
• Marzia Canzaniello (2023-2026)

Scientific Tutor of the following Research Fellow

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

International Visiting Ph.D. Students/Researcher/Lecturers @ M.O.D.A.L. research group

• Fatema Goulamaly, Université de Lorraine, France 2023
• Victor Rodriguez-Fernandez, Universidad Politécnica de Madrid, Spain 2022
• Rokas Gipiskis, Vilniaus Universitetas, Lituania, 2022-2023
• Zhengjing Ma, Beijing University of Geosciences, China, 2022
• Jiayu Qin, Beijing University of Geosciences, China, 2022

Master Thesis

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

• Giampaolo Casolla
• Fabio Giampaolo
• Edoardo Prezioso
• Danilo Crisci
• Andrea di Palma
• Stefano Izzo
• Federico Gatta
• Martina Savoia
• Daniela Annunziata
• Francesco Fato
• Gerardo Cappa
• Sara Amitrano
• Carlo Schiano di Cola
• Marco Preziosi
• Valeria Noviello