FISDeT: Fuzzy Inference System Development Tool. - Giovanna Castellano; Ciro Castiello; Vincenzo Pasquadibisceglie; Gianluca Zaza (Int. J. Comput. Intell. Syst., 2017)

A Fuzzy Rule-Based Decision Support System for Cardiovascular Risk Assessment. - Gabriella Casalino; Giovanna Castellano; Ciro Castiello; Vincenzo Pasquadibisceglie; Gianluca Zaza (WILF, 2018)

Using Convolutional Neural Networks for Predictive Process Analytics. - Vincenzo Pasquadibisceglie; Annalisa Appice; Giovanna Castellano; Donato Malerba (ICPM, 2019)

Evaluating End-User Perception Towards a Cardiac Self-care Monitoring Process. - Gabriella Casalino; Giovanna Castellano; Vincenzo Pasquadibisceglie; Gianluca Zaza (MobiHealth, 2019)

Contact-Less Real-Time Monitoring of Cardiovascular Risk Using Video Imaging and Fuzzy Inference Rules. - Gabriella Casalino; Giovanna Castellano; Vincenzo Pasquadibisceglie; Gianluca Zaza (Inf., 2019)

Predictive Process Mining Meets Computer Vision. - Vincenzo Pasquadibisceglie; Annalisa Appice; Giovanna Castellano; Donato Malerba (BPM (Forum), 2020)

A Hierarchical Fuzzy System for Risk Assessment of Cardiovascular Disease. - Gabriella Casalino; Riccardo Grassi; Marco Iannotta; Vincenzo Pasquadibisceglie; Gianluca Zaza (EAIS, 2020)

ORANGE: Outcome-Oriented Predictive Process Monitoring Based on Image Encoding and CNNs. - Vincenzo Pasquadibisceglie; Annalisa Appice; Giovanna Castellano; Donato Malerba; Giuseppe Modugno (IEEE Access, 2020)

Leveraging Multi-view Deep Learning for Next Activity Prediction. - Vincenzo Pasquadibisceglie; Annalisa Appice; Giovanna Castellano; Donato Malerba (ITBPM@BPM, 2021)

FOX: a neuro-Fuzzy model for process Outcome prediction and eXplanation. - Vincenzo Pasquadibisceglie; Giovanna Castellano; Annalisa Appice; Donato Malerba (ICPM, 2021)

Predictive Process Mining for Improving Business Process Management. - Vincenzo Pasquadibisceglie (BPM (PhD/Demos), 2022)

A multi-view deep learning approach for predictive business processes monitoring. - Vincenzo Pasquadibisceglie; Annalisa Appice; Giovanna Castellano; Donato Malerba (SERVICES, 2022)

A mobile app for contactless measurement of vital signs through remote Photoplethysmography. - Gabriella Casalino; Giovanna Castellano; Andrea Nisio; Vincenzo Pasquadibisceglie; Gianluca Zaza (SMC, 2022)

PROMISE: Coupling predictive process mining to process discovery. - Vincenzo Pasquadibisceglie; Annalisa Appice; Giovanna Castellano; Wil M. P. van der Aalst (Inf. Sci., 2022)

A Multi-View Deep Learning Approach for Predictive Business Process Monitoring. - Vincenzo Pasquadibisceglie; Annalisa Appice; Giovanna Castellano; Donato Malerba (IEEE Trans. Serv. Comput., 2022)

CENTAURO: An Explainable AI Approach for Customer Loyalty Prediction in Retail Sector. - Giuseppina Andresini; Annalisa Appice; Pasquale Ardimento; Andrea Antonio Brunetta; Antonio Giuseppe Doronzo; Giuseppe Ieva; Francesco Luce; Donato Malerba; Vincenzo Pasquadibisceglie (AI*IA, 2023)

DARWIN : An online deep learning approach to handle concept drifts in predictive process monitoring. - Vincenzo Pasquadibisceglie; Annalisa Appice; Giovanna Castellano; Donato Malerba (Eng. Appl. Artif. Intell., 2023)

STARDUST: A Novel Process Mining Approach to Discover Evolving Models From Trace Streams. - Vincenzo Pasquadibisceglie; Annalisa Appice; Giovanna Castellano; Nicola Fiorentino; Donato Malerba (IEEE Trans. Serv. Comput., 2023)

LUPIN: A LLM Approach for Activity Suffix Prediction in Business Process Event Logs. - Vincenzo Pasquadibisceglie; Annalisa Appice; Donato Malerba (ICPM, 2024)

A Stream Data Mining Approach to Handle Concept Drifts in Process Discovery. - Vincenzo Pasquadibisceglie; Donato Lucente; Donato Malerba (ISMIS, 2024)

Enhancing Next Activity Prediction with Adversarial Training of Vision Transformers. - Vincenzo Pasquadibisceglie; Annalisa Appice; Giovanna Castellano; Donato Malerba (SEBD, 2024)

JARVIS: Joining Adversarial Training With Vision Transformers in Next-Activity Prediction. - Vincenzo Pasquadibisceglie; Annalisa Appice; Giovanna Castellano; Donato Malerba (IEEE Trans. Serv. Comput., 2024)

${ sf PROPHET}$PROPHET: Explainable Predictive Process Monitoring With Heterogeneous Graph Neural Networks. - Vincenzo Pasquadibisceglie; Raffaele Scaringi; Annalisa Appice; Giovanna Castellano; Donato Malerba (IEEE Trans. Serv. Comput., 2024)

TSUNAMI - an explainable PPM approach for customer churn prediction in evolving retail data environments. - Vincenzo Pasquadibisceglie; Annalisa Appice; Giuseppe Ieva; Donato Malerba (J. Intell. Inf. Syst., 2024)

Data-Centric AI. - Donato Malerba; Vincenzo Pasquadibisceglie (J. Intell. Inf. Syst., 2024)

GANDALF: A LLM-based approach to map bark beetle outbreaks in semantic stories of Sentinel-2 images. - Vincenzo Pasquadibisceglie; Vito Recchia; Annalisa Appice; Donato Malerba; Giuseppe Fiameni (SAC, 2025)

Leveraging a large language model (LLM) to predict hospital admissions of emergency department patients. - Vincenzo Pasquadibisceglie; Annalisa Appice; Donato Malerba; Giuseppe Fiameni (Expert Syst. Appl., 2025)