Computer Science
Doctoral programme (PhD)
A.Y. 2024/2025
Study area
Science and Technology
PhD Coordinator
The doctoral programme in Computer Science aims to provide students with advanced scientific, methodological and technological knowledge in computer science and related sectors and their corresponding fields of application. This knowledge will prepare students and introduce them to theoretical and applied research, with particular attention to interdisciplinarity and internationalisation, developing research skills so that they are able to produce original independent research of interest to the international scientific community and businesses.
The doctoral programme aims to provide students with:
- solid wide-ranging knowledge on the basics of science and methodologies and technologies pertinent to IT and related fields,
- advanced and in-depth skills in specific areas,
- interdisciplinary skills necessary to promote cultural and methodological synergies,
- sound knowledge of research methodologies and of how to organise and manage research and disseminate results,
- opportunities to train internationally,
- a better preparation and placement within academic research groups and companies.
The doctoral programme aims to provide students with:
- solid wide-ranging knowledge on the basics of science and methodologies and technologies pertinent to IT and related fields,
- advanced and in-depth skills in specific areas,
- interdisciplinary skills necessary to promote cultural and methodological synergies,
- sound knowledge of research methodologies and of how to organise and manage research and disseminate results,
- opportunities to train internationally,
- a better preparation and placement within academic research groups and companies.
Tutte le classi di laurea magistrale - All classes of master's degree
Dipartimento di Informatica "Giovanni degli Antoni" - Via Celoria, 18 - Milano
- Main offices
Dipartimento di Informatica "Giovanni degli Antoni" - Via Celoria, 18 - Milano - Degree course coordinator: Roberto Sassi
[email protected] - Degree course website
http://www.di.unimi.it/ecm/home/didattica/dottorato/
| Title | Professor(s) |
|---|---|
| Certification of Machine Learning/Artificial Intelligence models.
Requirements: Knowledge of the main machine learning/artificial intelligence tecniques. Knowledge of the main assurance techniques. Knowledge of the main laws and regulations on AI (e.g., AI Act). |
|
| Enhanced Data Governance for Big Data Environments and Artificial Intelligence.
Requirements: Knowledge of the main big data and AI architectures and technologies. Knowledge of the main data governance solutions for big data architectures. Knowledge of Apache big data architecture. |
|
| Security Certification for IoT-edge Systems
Requirements: Knowledge of the main certification and assurance techniques. Knowledge of cloud-edge architectures and systems. |
|
| Non-functional verifications on 5G enabled Continuum Edge architecture
Requirements: Knowledge of the principal testing and monitoring techniques for non-functional assessment. Knowledge of the mobile telcomunication, Cloud and Edge architectures. |
|
| Sound synthesis and rendering for interaction
Requirements: Digital signal processing; Audio programming |
|
| Development and evaluation of accessible music interfaces
Requirements: Audio and MIDI programming; experimental methods in HCI |
|
| AI-based methods for autonomous planning with mobile robots and agents.
Requirements: Basics of algorithms, optimization, and machine learning |
|
| Inerpretable AI methods for human behavior recognition in sensorized environments
Requirements: Basis of Machine Learning, Python Programming |
|
| Abnormal behavior recognition in smart-home environments for digital health applications
Requirements: Basics of Machine Learning, Python Programming |
|
| Probabilistic integration of visual attention and language models
Requirements: Basic knowledge of statistics, statistical machine learning and computer vision |
|
| Inferential techniques for contextualizing affective models via language models
Requirements: Basic knowledge of statistics, statistical machine learning, affective computing, (biological, voice and video) |
|
| Geometric centralities
Requirements: Algorithms; graph theory |
|
| Innovative approaches on applied games for clinical treatment of children with disabilities based on integration of emotional intelligence, game design and machine learning.
Requirements: Statistics fundamentals |
|
| Personality and emotion models for interactive agents in VR environments.
Requirements: good skills in: - design and development of VR application for gaming - C++ - Machine Learning - Human-computer -interaction |
|
| Efficient algorithms for machine learning on graphs
Requirements: Foundations of machine learning. Design and analysis of algorithms. |
|
| Algorithms for sampling and counting in massive hypergraphs
Requirements: Solid theoretical foundations. Design and analysis of algorithms. |
|
| Graph-based analysis for biomedical data integration, prediction, and interpretation
Requirements: strong mathematical basis, machine learning, python, pytorch |
|
| Universal Language Server Protocol and Debugger Adapter Protocol for Modular Language Workbenches | |
| Data-driven agent based models in process simulation
Requirements: Basic notions of Process Mining and Agent-based Modeling |
|
| Large Scale Prescriptive Analytics: solving optimization problems in real contexts, where large scale, dynamic and heterogeneous data make classical techniques unsuitable
Requirements: Mathematical modeling, operations research, statistics, simulation, design and experimental analysis of algorithms |
|
| Data driven mathematical programming: integrating mathematical programming, machine learning, and probabilistic methods.
Requirements: Knowledge of Mathematical programming, statistics, machine learning, design and experimental analysis of algorithms |
|
| Privacy preserving machine learning and applications | |
| Secure computation techniques and blockchain applications | |
| Logic synthesis for emerging technologies | |
| Polynomial verification of Boolean circuits | |
| Algorithms for Combinatorial Optimization problems applied to complex decisions
Requirements: Algorithms and Data Structures, Operations Research, C programming |
|
| Discrete optimization algorithms for industrial applications
Requirements: Algorithms and Data Structures, Operations Research, C programming |
|
| Data security and privacy in emerging scenarios | |
| Less-constrained biometric recognition systems | |
| Security and privacy in biometric systems | |
| Investigating biases and ethical issues in NLP and visual transformers
Requirements: Background in artificial intelligence, natural language processing and/or visual transformers, and, optionally, in data ethics and the humanities |
|
| Controlled and collaborative query execution in emerging scenarios | |
| Semi-supervised learning based on parametric Hopfield networks for unbalanced data classification | |
| Improving scalability of large-scale agents simulations using parallel (GPU) and/or distributed programming
Requirements: advanced programming skills, with preference for CUDA and GPU programming |
|
| Unsupervised learning in artificial intelligence: learning from unlabeled data | |
| Less-constrained monitoring in Industry 4.0 by signal/image processing, artificial intelligence, and machine learning | |
| Artificial intelligence in healthcare and medicine
Requirements: AI, computer vision, signal processing |
|
| Non-convex optimizations in machine learning
Requirements: Optimization algorithms and signal processing |
|
| 3d point cloud: acquisition, segmentation and classification
Requirements: Artificial Intelligence, Computer Vision, Signal Processing |
|
| Exploring and Enhancing Smart Contract Security through Vulnerability Analysis
Requirements: Knowledge of the fundamentals of blockchain and smart contracts, understanding of basic attack/defense techniques in software security, good programming skills. |
|
| User empowerment in regulating private information release and assessing misinformation in online scenarios
Requirements: Basic knowledge of data protection (e.g., anonymization, privacy metrics, access control) and/or basic NLP algorithms and explainability mechanisms. |
|
| Advanced Digital Technologies for Music
Requirements: Basic knowledge in Computer Science (programming languages, databases, etc.) and Music (music theory, fundamentals of harmony). |
|
| Distributed architectures for entertainment applications
Requirements: networking, distributed systems |
|
| Models and methods for learning succinct data structures
Requirements: Machine Learning. Design and analysis of algorithm |
|
| Assistive technologies on mobile devices | |
| Data management and artificial intelligence in medicine | |
| Definition of hybrid models, that combine large language models, knowledge graphs and graph-based machine learning techniques, for the creation, enhancement and analysis of knowledge graphs
Requirements: Knowledge of graph-based data management systems, good knowledge of Machine learning techniques, good programming skills in python |
|
| formal verification of programming language theory
Requirements: functional programming, logic, theoretical computer science |
|
| Identify and overcome the main difficulties in learning to program | |
| Human-AI Collaborative Writing
Requirements: Knowledge on Natural Language Processing (NLP) |
|
| AI for sound and music computing
Requirements: Machine learning, statistical signal processing |
|
| Formal systems and complexity
Requirements: Automata and formal languages |
|
| Dependable and sustainable Cloud/Fog/Edge Computing: artificial intelligence for resource and task allocation for performance, energy consumption, fault tolerance, and resilience | |
| Intelligent systems for industrial and environmental applications based on IoT architectures and artificial intelligence | |
| Artificial Intelligence for Networking: designing of algorithms for the effective, anticipatory and automated orchestration of network resources.
Requirements: Artificial Intelligence/Machine Learning, Data Analysis, Wireless and Mobile Networks, Edge Computing , Simulation |
|
| Formal methods for Security- and Safety-critical Systems
Requirements: Skills in Formal Methods and Temporal Logics. Skills in security and safety |
|
| Applied formal methods in Digital Twins
Requirements: Skills in Formal Methods and Temporal Logics. Skills in security and safety |
|
| Optimization on networks
Requirements: Operations research, algorithms, computer programming |
|
| Optimization algorithms in logistics
Requirements: Operations research, algorithms, computer programming |
|
| Automatic generation of storytelling for video games based on playstiles and emotional reactions of players
Requirements: good skills in: game design and development AI for videogame HCI decision systems |
|
| Design and development of artificial intelligence algorithms for the analysis of cardiac arrhythmias
Requirements: Knowledge of signal processing and/or artificial intelligence are suggested |
|
| Color, design, simulation and accessibility in games | |
| A novel colorimetry based on human vision in context | |
| Data privacy and artificial intelligence | |
| Biomedical signal processing for a patient-centric digital health | |
| Ambient intelligence: data analysis and machine learning for self-adaptive environments | |
| Deep learning: learning techniques and explainability | |
| Optimization algorithms in logistics
Requirements: Operations research, algorithms, computer programming |
|
| AI methods for early diagnosis of tumor pathologies based on label-free images
Requirements: Basic knowledge of artificial intelligence |
|
| Phylogenetic tree reconstruction: algorithms and models | |
| Large Language Models for Molecular Biology and Medicine
Requirements: Machine Learning basics and programming skills in Python |
|
| High-speed cryptography
Requirements: Background knowledge: cryptography and algebra |
|
| Analysis of cryptographic primitives based on machine learning techniques
Requirements: cryptography and machine learning |
|
| Machine learning and network science for graph-based applications | |
| Artificial Intelligence applications to Vehicle Routing Problems (ex DM 630/2024)
Requirements: statistics, simulation, machine learning, operations research |
|
| Polynomial optimization techniques and their application to cryptographic primitives (ex DM 630/2024)
Requirements: Background knowledge: cryptography and algebra |
(IT Systems s.r.l.)
|
| Mixture of Open Source LLMs (ex DM 630/2024)
Requirements: Fundamentals of machine learning |
(S2E SPRINT S.r.l.)
|
Courses list
October 2024
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Resources Allocation in Mobile Edge Computing | 2 | 10 | Italian | |
November 2024
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Cyber Threat Intelligence: Challenges and Future Directions | 2 | 10 | English | |
| Foundations of Data and Knowledge Bases | 3 | 16 | English | |
January 2025
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Deep Learning for Signal and Image Processing | 2 | 10 | English | |
| Heuristic Algorithms for Combinatorial Optimization | 4 | 20 | English | |
| Introduction to Quantum Computing and Cryptography | 2 | 10 | English | |
| Mathematical Programming for Analytics | 3 | 15 | English | |
| Optimized Artificial Intelligence in Edge Computing and Iot | 2 | 10 | English | |
| Security Certification of Modern Systems: from Cloud Computing to Artificial Intelligence | 2 | 10 | English | |
March 2025
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Constructing and Mining Biomedical Knowledge Graphs | 4 | 20 | English | |
| Parameterized Algorithms | 3 | 15 | English | |
April 2025
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Artificial Intelligence in Biometrics | 2 | 10 | English | |
May 2025
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Complex Networks: an Interdisciplinary Approach to Study and Simulate Complex Systems | 4 | 20 | English | |
June 2025
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Data Privacy/security and Artificial Intelligence | 2 | 10 | English | |
Enrolment
Places available: 11
Call for applications
Please refer to the call for admission test dates and contents, and how to register.
Application for admission: from 29/05/2024 to 27/06/2024
Application for matriculation: from 09/08/2024 to 27/09/2024
Attachments and documents
Following the programme of study
Contacts
Office and services for PhD students and companies