Computer Science
Doctoral programme (PhD)
A.Y. 2021/2022
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) |
|---|---|
| Advanced assurance techniques for Big Data computations
Requirements: Cybersecurity and distributed architecture |
|
| Certification of Machine Learning/Artificial Intelligence models.
Requirements: Knowledge of the main machine learning/artificial intelligence tecniques. Knowledge of the main assurance techniques. |
|
| Sound synthesis and 3D rendering for Virtual and Augmented Realities
Requirements: Digital signal processing; Audio programming |
|
| Modeling room and listener acoustics for binaural sound rendering | |
| Development and evaluation of innovative music interfaces
Requirements: Audio and MIDI programming; experimental methods in HCI |
|
| AI-based methods for autonomous planning in multi-agent and multi-robot systems
Requirements: Fundamentals of algorithms, linear algebra, general knowledge of basic techniques in AI |
|
| Z-fast tries and other efficient data structures inspired from van Emde Boas trees | |
| Stochastic and variational approaches for Bayesian inference in intelligent systems
Requirements: Statistical machine learning, Probabilistic methods for computer science |
|
| Bayesian programming and Bayesian neural nets for computer vision and affective computing
Requirements: Statistical machine learning, Computer vision, Affective computing models |
|
| E-Health: integration of domotics, service robots, exer-games, virtual comunities 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. | |
| Multi-modal stimulation for treatment of autistic spectrum syndroms. Exer-games and music: development of models associated to music listening and applications to autism treatment. | |
| Modeling and learning from long-term cyclic environmental dynamics for autonomous mobile service robots using ML and AI. | |
| Neuropsychological Digital Cognitive Assessment of MCI | |
| Leveraging Machine Learning in Process Mining
Requirements: Computer Science Fundamentals and Programming |
|
| Online learning algorithms
Requirements: Basics of machine learning |
|
| Design and analysis of efficient machine learning algorithms
Requirements: Basics of machine learning |
|
| Data driven mathematical programming: integrating mathematical programming and machine learning
Requirements: Mathematical programming, statistics, machine learning, design and analysis of algorithms |
|
| Large Scale Prescriptive Analytics: solving complex optimization problems in real world contexts where large size, dynamic, heterogeneous data make classical techniques unsuitable
Requirements: Mathematical modeling, operations research, statistics, simulation, design and experimental analysis of algorithms |
|
| Advanced Computational Methods for Smart Industry
Requirements: Information Management, Advanced Computer Programming, Statistics, Mathematical Modeling |
|
| Explainable Computational Intelligence Models |
A. Ciaramella
|
| Secure computation and applications
Requirements: Basic cryptography |
|
| Blockchain: formal aspects and applications
Requirements: Cryptography |
|
| Circuit design for emerging technologies | |
| Approximate logic synthesis | |
| Algorithms for Combinatorial Optimization problems applied to complex decisions
Requirements: Algorithms and Data Structures, Operations Research, C programming |
|
| Testing Techniques and Methods Independent of the programming Language Used to Write the Software under Test | |
| Program synthesis applied to GPU/TPU and high performance computing with the help of automatic reasoning, constraint programming and property checking | |
| Understanding human mobility in complex spaces
Requirements: Programming skills |
|
| Mobility behavior in indoor spaces
Requirements: Programming skills |
|
| Data security and privacy in emerging scenarios | |
| Less-constrained biometric recognition systems | |
| Security and privacy in biometric systems | |
| Explainability of statistical and neural language models
Requirements: Preliminary knowledge of Natural Language Processing and machine learning |
|
| Controlled and collaborative query execution in distributed systems | |
| Machine learning methods for unbalanced data classification | |
| Algorithms for deep neural networks compression | |
| Machine Learning methods for Computational Biology | |
| Evolution of complex networks | |
| Unsupervised learning in artificial intelligence: learning from unlabeled data | |
| Less-constrained monitoring in Industry 4.0 by signal/image processing and machine learning | |
| 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
|
| Software Security, Protection and Analysis
Requirements: Good knowledge about code analysis techniques such as Program Analysis (e.g. Data Flow Analysis, Slicing, etc. ) and good knowledge about the attacks against vulnerabilities defined inside the code (e.g., Memory Errors, Web attacks etc.) |
|
| Computer-based technologies for music education
Requirements: Basic knowledge in computer science (programming languages, databases, etc.) and music (music theory, fundamentals of harmony, etc.) |
|
| Computer-based technologies for music-related cultural heritage
Requirements: Basic knowledge in computer science (programming languages, databases, etc.) and music (music theory, fundamentals of harmony, etc.) |
|
| Entertainment services provisioning in distributed environments
Requirements: Networking |
|
| Real-time profiling and verification of eSport players
Requirements: Programming, Machine Learning |
|
| Assistive technologies on mobile devices | |
| Data management and artificial intelligence in medicine | |
| Verification & validation in programming language theory
Requirements: Logic, declarative programming |
|
| Data Science for Computational Social Sciences and Humanities
Requirements: Solid background in computer science, with particular focus on machine learning and data management. |
|
| Deep learning for audio and music signal processing
Requirements: Audio signal processing, statistics, machine learning |
|
| To study new methods in distribuite algorithm design to move Robots in 3D, together with performance evaluation and comparison with sequential algorithms. | |
| Formal systems and complexity
Requirements: Automata and formal languages |
|
| Dependable Cloud/Fog/Edge Computing: resource and task allocation for fault tolerance, resilience and performance | |
| Intelligent systems for industrial and environmental applications based on IoT architectures and artificial intelligence | |
| Modeling and Verification of Self Adaptive Systems
Requirements: Skills in Formal Methods and Temporal Logics |
|
| Formal methods for Security- and Safety-critical Systems
Requirements: Skills in formal methods and in security |
|
| Procedural generation for story-driven video games based on playstyle and mood of players
Requirements: Good knowledge of game design and game programming |
|
| Advanced techniques for digital color restoration | |
| Image enhancement for medical imaging | |
| Data protection techniques for the digital data market | |
| Graph theory and signal processing for characterizing the heart's electrical activity during atrial arhythmias | |
| Analysis and development of diagnostic algorithms for the identification of atrial arrhythmias from electrocardiographic signals using machine learning techniques. | |
| Machine learning algorithms and biomedical signal processing for patient-centric digital health | |
| Ambient intelligence: data analysis and machine learning for self-adaptive environments | |
| Deep learning: learning techniques and explainability | |
| Explainable Artificial Intelligence for Precision Medicine
Requirements: Artificial Intelligence and Machine learning knowledge |
|
| Artificial Intelligence methods for the Network Medicine | |
| Blockchain-based online social media: a temporal and economic viewpoint | |
| High-speed cryptography
Requirements: Background knowledge: cryptography and/or algebra |
|
| Cryptanalysis
Requirements: Background knowledge: cryptography and/or algebra |
Courses list
November 2021
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Ai Methods for Sensor-Based Activity Recognition and Context-Awareness | 2 | 10 | English | |
| Online Learning: Theory and Algorithms | 2 | 10 | English | |
December 2021
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Security, Privacy and Data Protection | 4 | 20 | English | |
January 2022
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Artificial Intelligence for Network Medicine | 4 | 20 | English | |
| Data Visualization | 2 | 10 | English | |
| Leveraging Machine Learning in Process Mining | Gianini Gabriele
|
2 | 10 | English |
| Methods for Statistical Model Fitting | 2 | 10 | English | |
February 2022
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Advanced Topics in Signal Processing | 2 | 10 | English | |
| Introduction to Interactive Theorem Proving with Coq | 2 | 10 | English | |
| Matheuristics for Combinatorial Optimization Problems (Module 1) | 2 | 10 | Italian | |
| Matheuristics for Combinatorial Optimization Problems (Module 2) | 2 | 10 | Italian | |
| Network Design (modeling, analysis and optimization of networks part 2) | 2 | 10 | English | |
May 2022
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Finite Memory Quantum Computational Devices: from Theory to Practice | 2 | 10 | English | |
| Systematic Debugging Techniques | 2 | 10 | English | |
June 2022
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Privacy and Anonymity in Data Release | 2 | 10 | English | |
| Resources Allocation in Mobile Edge Computing | 2 | 10 | English | |
| Smart Data Integration and Processing On Service Based Environments: Issues, Challenges & Contributions. | 3 | 16 | English | |
August 2022
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Recent Advancements in Artificial Intelligence: Theoretical Foundations, Methodologies, Technologies, and Applications | 6 | 30 | English | |
Following the programme of study
Contacts
Office and services for PhD students and companies