CV
You can explore my full professional background below or download a one-page PDF version for offline viewing.
📄 Download CV (PDF)Skills
- Pipelines
- API: Websockets and Rest
- Databases: Microsoft and InfluxDB
- Ingestion: Node-Red, MQTT
- Data Analysis, ML Ops & Software
- Programming: MATLAB and Python
- Libraries: Pytorch, TensorFlow and Scikit-learn
- Dashboard: Dash, Streamlit, Django, React and Grafana
- Containers: Docker
- Versioning: GitHub
- Cloud Environments
- Azure: Databricks and Data Factory
- Amazon: Routing services
- Heroku
- Google Cloud Platform
- Operative Systems
- Ubuntu
- Windows
Work experience
2026-present: Postdoctoral Research Fellow, Brighton University, Brighton
2025–2026: Digital Transformation Lead, Newcastle University, Newcastle Upon Tyne
Position funded by Innovate UK as a Knowledge Transfer Partnership associate with Newcastle University and Merit.- Process optimization: Translating manufacturing operational needs into digital transformation requirements.
- Product owner: Development and coordination of PowerApps (e.g., MES solutions) to improve the operational visibility of manufacturing shop floors.
- ETL pipelines: Implementation of workflows to store manufacturing-driven data streams into databases.
- Data mining: Development of feature-extracted datasets by fusing manufacturing and design data. These data streams are leveraged by machine and deep learning models to improve production monitoring, planning, and scheduling.
- Experimental campaign: Coordination of large teams and 30+ stakeholders ranging from C-level executives to shop floor workers to deploy digital transformation manufacturing architectures.
- Dashboard: Design and development of data analytics platforms to turn manufacturing data into actionable KPIs and improve manufacturing monitoring and planning.
2021-2025: PhD Candidate, University of Trento, Chair: Manufacturing Systems
- Thesis: Cyber-physical systems to monitor the efficiency and sustainability of human-centric manufacturing systems.
- IoT sensor: Deployment of human-centric digital technologies to monitor manual task executions and safety of workers in industrial scenarios. Hands-on with many sensors such as RTLS (UWB), Inertial Measuring Units, Azure Kinect, RFID readers, and Electromyography. Responsible for designing the desired data flow and storage based on business requirements.
- ML frameworks/pipeline: Applied ML algorithms to pre-processed and feature-extracted data, enabling target-oriented decision-making. Training, fine-tuning, and inference of PyTorch algorithms (supervised and unsupervised) in Jupyter Notebooks and HPC cluster.
- Experimental campaign: Managing mid-term projects with plant supervisors to meet milestones and business goals. Responsible for architecture installation, data acquisition, and storage. Involvement of 70+ workers in production and logistics environments of both SMEs and multinational companies.
- Dashboards: Delivering actionable KPIs and KRIs to drive strategic process monitoring and enable efficiency and safety-related business optimizations.
- Supervision: Technical support and mentoring of students for Master’s, Bachelor thesis, and freshman Ph.D. students.
- Dissemination: Deliver engaging presentations to both technical and non-technical audiences at major conferences, enhancing the team’s visibility and attracting potential new collaborations.
2023: Visiting PhD Candidate, University of Twente, Chair: Manufacturing Systems
- Project: Development of a cyber-physical architecture to monitor human-centric reconfigurable manufacturing systems (RMS)
- IoT sensor: Design, installation, and test of an UWB-based RTLS to monitor industrial entities and the workforce in a RMS set-up
- ML frameworks/pipeline: Applied ML algorithms to pre-processed and feature-extracted data, enabling target-oriented decision-making. Training, fine-tuning, and inference of PyTorch algorithms (supervised and unsupervised) in Jupyter Notebooks.
- Experimental campaign: Managed more than 40+ students across 8 production set-up, resulting in a dataset of more that 1M input data.
- Dashboards: Delivering actionable KPIs to monitor the efficiency and social sustainability of RMS environments.
- Supervision: Technical support and mentoring of Learning Factory students.
2020-2021: Research Assistant, University of Göttingen, Chair: Production and Logistics
- Support: Lecture preparation and student mentoring and support throughout the course
- Laboratory: Delivered 8 hours of lectures utilizing simulation tools to address real-world case applications
- Research Project: Literature review on the usage of indoor positioning systems in manufacturing and logistics environments
Education
- MBA in Business Administration, London School of Economics, 2025
- M.Sc. in Management Engineering, University of Bologna, 2018-2021
- B.S. in Management Engineering, University of Bologna, 2015-2018
Certifications
- CMI Level 5 in Management and Leadership, Ashorne Hill, 2025
- Computer Vision Fundamentals with Google Cloud, Google Cloud Skills Boost, 2024
- Machine Learning, Stanford University, 2020
