Computer Science
Doctoral programme (PhD)
A.Y. 2022/2023
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) |
|---|---|
| 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 telecommunication, Cloud and Edge architectures. |
|
| Enhanced Data Governance for Big Data Environments
Requirements: Knowledge of the main big data architectures and technologies. Knowledge of the main data governance solutions for big data architectures. Knowledge of Apache big data architecture. |
|
| Certification of Machine Learning/Artificial Intelligence models
Requirements: Knowledge of the main machine learning and artificial intelligence techniques. Knowledge of the main assurance techniques |
|
| Cloud-edge infrastructure and service certification
Requirements: Knowledge of the main techniques for certification and assurance of non-functional properties. Knowledge of cloud-edge infrastructure and services. |
|
| A novel data governance and assurance framework for ML-based, data intensive systems
Requirements: Knowledge of the main data governance and assurance solutions for ML-based data intensive systems. Knowledge of Apache big data architecture. |
|
| Sound synthesis and 3D rendering for Virtual and Augmented Realities
Requirements: Digital signal processing; Audio programming |
|
| Development and evaluation of innovative music interfaces
Requirements: Audio and MIDI programming; experimental methods in HCI |
|
| Development of a digital ecosystem for music making with different types of disabilities
Requirements: Audio programming; experimental methods in HCI |
|
| Methods for autonomous planning with mobile robots and agents
Requirements: Basics of algorithms, optimization, and machine learning |
|
| Data privacy in pervasive digital health | |
| Centrality axioms of directed and undirected networks | |
| E-Health: integration of domotics, service robots, exer-games, virtual communities and web services through intelligent systems and emotional intelligence to support pre-frail people at home. | |
| Development of deep neural networks based on convolutional layers for reinforcement learning: extraction of state-action patterns from applications in different domains. | |
| Modeling and learning from long-term cyclic environmental dynamics for autonomous mobile service robots using ML and AI. | |
| Multi-modal stimulation for treatment of autistic spectrum syndromes through exer-games that combine through an intelligent engine game design, music and emotional intelligence adapted to the user state. | |
| Innovative approaches on applied games for clinical treatment of children with disabilities based on integration of emotional intelligence, game design and machine learning. | |
| Embedded Systems Cybersecurity (Ex DM 352/2022) | |
| Graph Representation Learning methods for Precision Medicine
Requirements: A basic background in machine learning |
|
| Object-centric Process Mining
Requirements: Basic notions about Process Mining, Machine Learning, and Graph Databases |
|
| Causal Inference for Actionable Healthcare
Requirements: Basic notions of statistical inference and machine learning |
G. Gianini
|
| Weakly supervised machine learning algorithms
Requirements: Machine learning, analysis of algorithms |
G. Pasi (Università Milano-Bicocca)
|
| Online Decision Making through Interactions with a Non-Stationary Environment
Requirements: Machine learning, analysis of algorithms |
|
| Data driven mathematical programming: integrating mathematical programming, machine learning and probabilistic methods
Requirements: Mathematical programming, statistics, machine learning, design and experimental analysis of algorithms |
|
| 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 |
|
| Modulating of security repartees and application of distributed ledgers | |
| Privacy preserving techniques based on machine learning for malware detection | |
| Circuit design for emerging technologies | |
| Logic synthesis as information security enabler | |
| Algorithms for Combinatorial Optimization problems applied to complex decisions
Requirements: Algorithms and Data Structures, Operations Research, C programming |
|
| Discrete optimization algorithms for industrial applications Algorithms and Data Structures, Operations Research, C programming | |
| Techniques and concepts for indoor movement learning
Requirements: Programming skills, basics of data science |
|
| Data security and privacy in emerging scenarios | |
| Less-constrained biometric recognition systems | |
| Security and privacy in biometric systems | |
| Deep Learning methods for Natural Language Processing
Requirements: Preliminary knowledge of Natural Language Processing and machine learning |
|
| Models and techniques for learning succinct data structures | |
| Controlled and collaborative query execution in distributed systems | |
| Machine learning on temporal and multilayer networks | |
| Unsupervised learning in artificial intelligence: learning from unlabeled data | |
| Less-constrained monitoring in Industry 4.0 by signal/image processing and artificial intelligence | |
| Computational intelligence and applications
Requirements: Skills in Probabilistic Modeling and Data Analytics. Basic knowledge of Machine Learning. Familiarity with C/C++ and Python |
G. Gianini
|
| Big Data Modeling and Analytics
Requirements: Skills in Probabilistic Modeling and Data Analytics. Basic knowledge of Machine Learning. Familiarity with C/C++ and Python. |
G. Gianini
|
| Understanding human social communication based on complex facial signals
Requirements: Computer vision, signal processing, machine learning |
|
| Computer vision and affective computing models for human behavior analysis
Requirements: Artificial intelligence, Computer Vision, Affective Computing |
|
| Computing education and computational thinking: pedagogical approaches, teaching strategies, assessment. | |
| Advanced technologies for music education
Requirements: High computer skills and basic knowledge of musical aspects |
G. Haus
|
| Advanced technologies for music cultural heritage
Requirements: High-level computer skills and basic knowledge of music |
G. Haus
|
| Machine learning for audio and music signal processing
Requirements: Machine learning, statistics, signal processing |
|
| Entertainment services provisioning in distributed environments
Requirements: Networking |
|
| Streaming of interactive 3D virtual environments
Requirements: Networking, graphics, virtual reality |
|
| Machine learning techniques and models for fuzzy sets | |
| Assistive technologies on mobile devices | |
| Data management and artificial intelligence in medicine | |
| Constructing Knowledge Graphs for biomedical applications
Requirements: Knowledge of graph-based data management systems (e.g. neo4j), good knowledge of Machine learning techniques, good programming skills in python |
|
| Verification and validation in the semantics of programming languages
Requirements: functional programming, first-order logic |
|
| Identify and overcome the main difficulties in learning to program
Requirements: Teaching experience (in computer science) in K-12 education |
|
| Data Science for Computational Social Sciences and Humanities
Requirements: Solid background in computer science, with particular focus on machine learning and data management. |
|
| Algorithms for Distributed Systems
Requirements: Classical and distributed algorithms |
|
| 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 | |
| Formal methods for Security- and Safety-critical Systems
Requirements: Skills in Formal Methods and Temporal Logics. Skills in security and safety |
|
| Mathematical programming algorithms for NP-hard optimization problems
Requirements: Algorithms and data-structures, Operations research |
|
| Optimization methods in logistics
Requirements: Algorithms and data-structures, Operations research |
|
| Graph-based algorithms for the analysis of cardiac arrhythmias
Requirements: Knowledge of signal processing and graph theory are recommended. |
|
| Research and development of algorithms based on graph-neural networks for the analysis of biomedical signals and images (Ex DM 352/2022)
Requirements: Knowledge about machine learning is recommended. |
|
| Advanced models for color deficiencies description | |
| Energy-efficient secure and private distributed data management and processing | |
| Biomedical signal and image processing for a patient-centric digital health | |
| Ambient intelligence: data analysis and machine learning for self-adaptive environments | |
| Deep learning: learning techniques and explainability | |
| Innovative models for surface parametrization, for Geometry Processing and Computer Graphics
Requirements: Computer Graphics OR Geometry Processing |
|
| Tools for 3D asset-creation pipeline for Videogames
Requirements: Computer Graphics OR Geometry Processing OR Computer Animation |
|
| Graph deep neural networks | |
| The security of crypto building blocks
Requirements: Background knowledge: cryptography and algebra |
|
| High-speed cryptography
Requirements: Background knowledge: cryptography and algebra |
|
| Open source and cryptography to enhance the security of mobile devices
Requirements: Background knowledge: cryptography, security and computer programming |
|
| Graph mining on Web3 Social Media
Requirements: Strong background in Network Science |
|
| Multi-Task Reinforcement Learning with Constraints: Online Decision Making through Interactions with a Non-Stationary Environment (Ex DM 352/2022) | |
| Development of a digital ecosystem for music making with different types of disabilities (Ex DM 352/2022) | |
| Open source and cryptography to enhance the security of mobile devices (Ex DM 352/2022) | |
| A novel data governance and assurance framework for ML-based, data intensive systems (Ex DM 352/2022) | |
| Performance test and benchmarking of big data architectures (hyperscale) (EX DM 352/2022) | |
| Certification of machine learning models (EX DM 352/2022) | |
| Smart data-intensive service composition in cloud-edge continuum (Ex DM 352/2022) |
Courses list
October 2022
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Security Certification: from Traditional Software and Cloud System to Ml-Based Services | 3 | 15 | English | |
November 2022
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Distributed Models, Madrepuce and Large Scale Algorithms | 3 | 10 | English | |
January 2023
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Deep Learning for Signal and Image Processing | 2 | 10 | English | |
| Dynamic Programming | 2 | 10 | Italian | |
| Heuristic Algorithms for Combinatorial Optimization Problems | 4 | 20 | Italian, English | |
| Introduction to Quantum Information and Cryptography | Gianini Gabriele
|
4 | 20 | English |
February 2023
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Network Flows (modeling, analysis and optimization of networks part 1) | 2 | 10 | English | |
| Probabilistic Model Checking for Complex, Self-Organising Systems | 4 | 21 | English | |
March 2023
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Constructing and Mining Biomedical Knowledge Graphs | 4 | 20 | English | |
| Parameterized Algorithms, Parameterized Complexity, and Fixed-Parameter Tractability | 3 | 15 | English | |
April 2023
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| An Introduction to Category Theory | 2 | 10 | English | |
| User Study Experimental Design | 2 | 10 | Italian | |
June 2023
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Reversible Logic and Quantum Computing | 2 | 10 | English | |
July 2023
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| User Support for Data Protection in Emerging Scenarios | 2 | 10 | English | |
Following the programme of study
Contacts
Office and services for PhD students and companies