Francesco Congiu
Teaching Assistant @Università Degli Studi Di Cagliari
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WORK HISTORY
Teaching Assistant @Università Degli Studi Di Cagliari
Preparing comprehensive Python hands-on notebooks to complement theory lessons and explaining them during practice sessions. The notebooks include theoretical explanations, implementations of studied algorithms, and problem-solving challenges (LeetCode-style problems). The covered topics are Python language introduction, Recursion, Divide and Conquer, Search and Sorting algorithms, Stacks, Queues, Linked Lists, Hashmaps and Sets, Binary Search Trees, Heaps and Priority Queues, Dynamic Programming, Greedy Algorithms, Graph Theory, Shortest Path problems, and String Matching.
EDUCATION
Università degli Studi di Cagliari
Doctor of Philosophy - PhD, Teaching and Learning Science - STEM Education
IT Minerario Asproni - Fermi
Diploma, Computer Science and Telecommunications
Università degli Studi di Cagliari
Master's Degree, Applied Artificial Intelligence
Università degli Studi di Cagliari
Bachelor's Degree, Computer Science
ABOUT FRANCESCO CONGIU
I am a PhD Student specializing in RAG Systems, currently based at the TAIL (Trustworthy and Artificial Intelligence Laboratory), University of Cagliari. I conduct my research under the supervision of Prof. Ludovico Boratto and Prof. Mirko Marras, focusing on the intersection of Information Retrieval, Natural Language Processing, and Privacy-Preserving AI, applied to Educational and Professional contexts.My academic journey culminated in a Master’s Degree in Computer Science with full marks and honors (110/110 cum Laude). During my thesis, I designed and validated RetrievEM, a novel Retrieval-Augmented Generation (RAG) framework that integrates the Expectation-Maximization algorithm to strictly enforce document confidentiality without compromising retrieval quality.Previously, I built a strong engineering foundation as a Full Stack Developer, working on complex web architectures using the.NET ecosystem and SQL Server. This dual background allows me to bridge the gap between theoretical AI models and robust, scalable software implementations. Open to research collaborations and academic networking.
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