Angelo Leogrande
Papers
1
Total Citations
2
H-Index
1
About
Angelo Leogrande is a researcher whose work sits at the intersection of process engineering, digital transformation, and applied artificial intelligence. His primary research areas include business process modeling, AI-driven sales prediction, and the digitalization of small and medium-sized enterprises (SMEs). Leogrande’s major contribution lies in demonstrating how traditional production processes can be systematically redesigned using tools like Business Process Modelling Notation (BPMN) and then enhanced with predictive AI models to improve operational efficiency and decision-making. His case study on an Italian textile company, which has garnered 2 citations, exemplifies this approach by showing how digital technologies can be integrated into legacy manufacturing workflows. While his citation count is still growing, this work is notable for its practical focus on real-world SME challenges, offering a replicable framework for process innovation. Leogrande’s research is particularly valuable for students and practitioners interested in bridging the gap between engineering methodologies and AI applications in industrial contexts.
Research Focus
Key Achievements
Top Papers
- 1