Profile
Applied Computer Science and Data Analytics graduate with solid programming foundations and a strong interest in software engineering, AI, and technical problem solving. Built MUVAD, an end-to-end multimodal video anomaly detection framework, covering system design, implementation, model integration, and a web interface for results analysis. Hands-on experience with Python, C, JavaScript, SQL, Git, Linux, and Docker. Seeking a junior software engineering role where I can contribute to reliable applications, systems, and data pipelines.
Projects
- Built an end-to-end framework for automatic video anomaly detection using multimodal large language models
- Designed and implemented an integrated pipeline for video processing, model inference, and natural language explanations
- Developed a web interface for video upload, result visualization, and explanation analysis
- Achieved competitive benchmark results, reaching up to 83.17% AUC on UCF-Crime
- Repository: github.com/Zer0codestuff/MUVAD
- Technologies: Python, PyTorch, TensorFlow, Computer Vision, Multimodal LLMs
Education
University of Cagliari - Final grade: 109/110
- Thesis: developed an end-to-end framework for explainable video anomaly detection based on multimodal LLMs, with competitive results on UCF-Crime and XD-Violence
ITI Tortoli - Electronics and Electrical Engineering - Final grade: 100/100
Work Experience
Aequor srl - Baunei, Italy
- Supported daily operations in a 3-person team managing a fleet of 6 boats during peak season
- Used Excel to track bookings, availability, and revenue, helping organize day-to-day operations
- Assisted Italian and international customers, delivering technical and safety briefings in Italian and English