Research Trainings & Activities
This page summarizes my research activities, international collaborations, doctoral training, industrial placements, conference participation, and contributions to European research projects during my PhD in Computer Science at the University of Torino.
🇪🇺 EU Project — DistriMuSe
Distributed Multi-Sensor Systems for Human Safety and Health
Research activities focused on:
- Explainable AI for robotics safety
- Visual anomaly detection
- Human–robot collaboration
- Synthetic data generation
- ROS2-based industrial AI systems
| Date | Activity |
|---|---|
| Nov 2025 | Presented project updates through a 5-minute technical talk and poster presentation at the DistriMuSe consortium meeting hosted by the University of Vigo, Spain.  |
| May 2025 | Presented progress on anomaly detection and ADVIS integration during the consortium meeting hosted by Brno University of Technology, Czech Republic. |
| Jan–Aug 2025 | Visiting researcher at ValeriaLab, University of Granada, Spain, working on synthetic industrial data generation and explainable anomaly detection for robotics safety. |
| Nov 2024 | Participated in the DistriMuSe consortium meeting in Stuttgart, Germany. |
Project Website ValeriaLab ADVIS Repository
🇪🇺 EU Project — NextPerception
Research focused on:
- Explainable Artificial Intelligence (XAI)
- Trustworthy computer vision
- Improved LIME explanations
- Visual interpretability in AI systems
| Date | Activity |
|---|---|
| Feb 2024 | Contributed to Explainable AI research by improving LIME Image explanations using stratified sampling; research presented at AAAI 2024, Vancouver, Canada. |
Project Website LIME Stratified PyPI
📄 Research Highlights
AAAI 2026 — ShapBPT
ShapBPT: Image Feature Attributions using Data-Aware Binary Partition Trees
Accepted in the Main Track of the AAAI Conference on Artificial Intelligence 2026.
PDF arXiv Code Tests PyPI Project Page
ICPE / QualITA 2026
ShapBPT in Perspective: A Consolidated Review and an eXplainable Anomaly Detection Case Study
XAI-World 2024
Can I Trust My Anomaly Detection System? A Case Study Based on Explainable AI
AAAI 2024
Using Stratified Sampling to Improve LIME Image Explanations
PDF Code Examples PyPI Project Page
🎓 Doctoral Research & Training
| Date | Activity |
|---|---|
| Apr 2026 | Successfully defended the PhD thesis: Improving Trust in Safety-Critical AI Systems: Explainable AI and Anomaly Detection Frameworks for Human Safety in Smart Industries. |
| Jan–Aug 2025 | Erasmus+ international mobility period at the University of Granada, Spain. |
| Oct–Dec 2024 | Industrial research placement at RuleX Innovation Labs, Italy. |
| Oct 2023–Jan 2024 | Initial industrial placement at RuleX Innovation Labs focused on trustworthy AI for industrial applications. |
| Apr 2024 | Presented doctoral research at the COMETE PhD Workshop, University of Torino. |
Erasmus+ Certificate COMETE Workshop PhD Thesis
🌍 Conferences, Schools & Workshops
| Event | Location | Date | Links |
|---|---|---|---|
| Oxford Machine Learning Summer School | Oxford, UK | Jul 2024 | Certificate |
| XAI-World 2024 | Valletta, Malta | Jul 2024 | Certificate |
| AAAI 2024 | Vancouver, Canada | Feb 2024 | Certificate |
| ECML-PKDD 2023 | Turin, Italy | Sep 2023 | Certificate |
📘 Courses & Training 🏅 Certifications
🧠 Summary of Contributions
- Developed ShapBPT (AAAI 2026) for hierarchical image explanations
- Improved LIME explanations through stratified sampling
- Worked on Explainable AI for anomaly detection systems
- Built real-time ROS2-based industrial anomaly detection pipelines
- Contributed to EU research projects including DistriMuSe and NextPerception
- Completed international mobility and industrial research placements
- Developed explainable AI frameworks for human–robot safety