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Cosimo Laneve

Full Professor

Department of Computer Science and Engineering

Academic discipline: INF/01 Informatics


Tesi di Laurea Magistrale (NUOVE: 19/9/2023)

1) TECHNIQUES BASED ON MACHINE LEARNING FOR DERIVING CODE SIMILARITIES. Code is extremely fragile: e.g. swapping two lines of code changes completely its semantics. I want to devise machine learning techniques that are trained with abstract models of the codes and are able to derive similarities (and therefore detect plagiarism, bugs, malicious snippets). Then I want to study how much robust the technique is by perturbing codes in input (with automatic tools).


2) ALGORITHMS FOR SUSTAINABLE SUPPLY CHAINS. Shareholders, consumers, and employees have increasingly high expectations of the businesses they invest in, buy from, and are employed by. As a result, business leaders face more pressure from regulators and the market to prove that their organizations are acting responsibly and sustainably. I want to study techniques for, e.g., decarbonizing supply chains acting proactively on logistics or identifying opportunities for reducing waste or looking for alternative raw material with a lower environmental impact. The technologies should also create transparency of the performance of Environmental, Social and Governance (ESG) commitments.



Published on: September 19 2023