For students (thesis)

Available theses

This is a short list of topics which I am currently interested to work on. I am also open to supervise other thesis in the area of Automated Data Governance and Business Process Compliance.

It’s also possible to carry out theses in collaboration with companies.

In any case, please contact me by e-mail to schedule an appointment.

Automated Data Governance

Data Mesh is an emerging paradigm for cross-organizational data sharing, emphasizing domain-oriented ownership, self-service data infrastructure, and decentralized governance. In multi-organization contexts, ensuring compliance with agreements on privacy, performance, visibility, and other constraints is crucial. Monitoring data exchanges and detecting potential violations are key challenges.
Emerging approaches, including federated governance models, AI-driven policy enforcement, and LLM-based automation, offer innovative ways to address these challenges.
We propose the following thesis tracks:

  • Automated Policy Enforcement in Data Mesh: AI-driven Approaches
    • Explore how AI techniques, including Large Language Models (LLMs), can support automatic policy enforcement in Data Mesh architectures.
    • Automate tasks such as data classification, tagging, and compliance verification (privacy, access control, retention).
    • Investigate mechanisms for explainability and accountability to ensure transparency of automated governance.
  • AI-driven Policy Generation for Data Mesh Monitoring using OPA
    • Design a system for monitoring cross-organizational data sharing in a Data Mesh environment, ensuring compliance with agreements on privacy, performance, and visibility.
    • Use LLMs to automatically generate Rego policies for the Open Policy Agent (OPA) from textual descriptions of agreements and constraints.
    • Integrate the generated policies into OPA to monitor REST-based data services in real time.
    • Evaluate the system for accuracy, completeness, and effectiveness in detecting compliance violations.
  • Expected Outcomes (for both thesis):
    • Prototype systems or frameworks supporting distributed Data Mesh governance.
    • Guidelines and best practices for balancing domain autonomy and compliance.
    • Evaluation metrics for monitoring quality, privacy, performance, and policy enforcement.
    • Original contributions to research on scalable, automated, and AI-driven governance in decentralized data architectures.

Multi-party Business Process Compliance

Business Process Management (BPM) is increasingly moving toward inter-organizational scenarios, where multiple organizations collaborate through choreographic protocols. In these contexts, ensuring compliance—the adherence to regulations, contractual obligations, and governance policies—becomes crucial.
Emerging technologies offer innovative tools to address this challenge:

  • Blockchain, enabling transparency, immutability, and automated compliance checks through smart contracts.
  • Large Language Models (LLMs), which can support the extraction and verification of compliance rules from complex regulatory texts.

We propose the following thesis tracks:

  • Automatic Compliance in Choreographic BPM Protocols through Blockchain
    • Translation of compliance rules into smart contracts for distributed auditing.
    • Analysis of scalability, transparency, and privacy trade-offs.
    • Application to a case study (supply chain, healthcare, logistics).
  • LLMs as “Compliance Advisors” for Choreographic BPM Protocols
    • Use of language models to extract constraints from regulatory texts.
    • Automatic analysis of process execution logs to detect violations.
    • Evaluation of reliability and explainability of LLMs in governance scenarios.
    • Case study on banking protocols, GDPR, or healthcare compliance.
  • Expected Outcomes (for both theses):
    • A prototype software tool supporting compliance in choreographic protocols.
    • A critical evaluation of the chosen technology (blockchain or LLM).
    • An original contribution to the study of distributed governance in business processes.

Sequenzializzazione degli ordini di produzione su macchine utensili nel MES MaDS: progettazione, sviluppo e analisi prestazionale data-driven

MaDS è il MES di NEALIS (https://nealis.it/), una piattaforma modulare pensata per connettere ERP, reparti e macchine, raccogliendo eventi di produzione in tempo reale. La tesi propone la progettazione e lo sviluppo di un modulo software che sia in grado di sequenzializzare gli ordini di produzione su macchine utensili. Dato un insieme di ordini (con attributi come quantità e tempi ciclo teorici), un obiettivo primario (rispetto della date di fine produzione) e vincoli operativi (compatibilità ordine-macchina, calendari di disponibilità, esecuzione concorrente di più ordini), il modulo assegna gli ordini alle risorse e genera una sequenza ottimizzata. L’approccio prevede modelli di scheduling vincolato e/o euristiche migliorative, con valutazione tramite KPI (ritardo, utilizzo macchina, throughput). In parallelo, viene sviluppato uno strumento di analisi che sfrutta i dati del MES per determinare i tempi ciclo reali per articolo e risorsa, confrontarli con i teorici e identificare le macchine più performanti. Il risultato è un ciclo chiuso pianificazione-misura-adattamento, a supporto di decisioni di produzione affidabili e data-driven.

Lo stack tecnologico utilizzato si basa su:

  • Linguaggi di sviluppo PHP (Lavarel/Symfony) + javascript (Backbone.js, Bootstrap e Vue.js)
  • Database relazionale PostgreSQL
  • Database NoSQL MongoDB e Redis
  • OS Linux
  • Virtualizzazione docker
  • Source management git (Bitbucket)

Il lavoro è adatto per una tesina e si svolgerà in collaborazione con l’azienda Nealis

Useful material

The School of Industrial and Information Engineering has developed a template for the thesis document in both Latex and Word format. Students are invited to produce final documents compliant with these templates which can be downloaded from https://www.ingindinf.polimi.it/it/didattica/lezioni-e-esami/esami-di-laurea-e-laurea-magistrale . In case you would like to use Overleaf to edit the Latex version, the template is also available in the gallery https://www.overleaf.com/latex/templates/classical-format-thesis-scuola-di-ingegneria-industriale-e-dellinformazione-politecnico-di-milano/dkmvtndqkyxg