ResearchJul 2026
Research Intern — Neural Network Verification
The Digital Research Center of Sfax (CRNS) · Sfax, Tunisia
- Evaluated the certified robustness of convolutional neural networks on the VNN-COMP CIFAR2020 benchmark with α,β-CROWN — 147 properties under L∞ perturbations (ε = 2/255 and 8/255).
- Reproduced the official competition verdicts with 93.2% agreement (137 / 147), including all 103 certified-safe (UNSAT) instances; divergences clustered near the 300 s timeout.
- Automated parsing and analysis of α,β-CROWN verification logs in Python, extracting verdicts, runtimes, and Branch-and-Bound statistics into structured reports.
- Investigated Branch-and-Bound behaviour and robustness under different perturbation budgets, and built a PySide6 GUI to drive verification experiments from one place.
- α,β-CROWN
- Certified Robustness
- VNN-COMP
- Python
- PySide6