Computer science
Doctoral programme (PhD)
A.Y. 2019/2020
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
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: Paolo Boldi
paolo.boldi@unimi.it - Degree course website
http://dottorato.di.unimi.it/
| Title | Professor(s) |
|---|---|
| An assurance monitoring technique for the cloud based on big data analytics
Requisiti: Cloud Architecture, basic notions of Big Data Pipelines, basic notions of Computer Security |
|
| Assurance Techniques for the Internet of Things.
Requisiti: Knowledge of the main cloud and IoT technologies. |
|
| Development and validation of innovative music interfaces
Requisiti: Audio and MIDI programming; Experimental methods in HCI |
|
| Sonic interaction design and assistive technologies for blind and visually impaired users
Requisiti: Audio and MIDI programming; experimental methods in HCI |
|
| Advanced techniques for sound synthesis and 3D rendering in interactive contexts
Requisiti: Digital signal processing, audio programming |
|
| Multi-level navigation in musical contents |
A. Baratè
|
| AI techniques for sensor-based human activity recognition | |
| Personal Data Protection in Smart Environments
Requisiti: Data Security & Privacy; Distributed Systems; IOT |
|
| Digital health applications of intelligent pervasive systems | |
| Stochastic models for latent variable dynamical systems with application to affective computing and visual attention
Requisiti: Stochastic processes, Computer Vision, Affective computing, Statistical methods for machine learning |
|
| E-Health: integration of domotics, service robots, exer-games, virtual comunities and web services through intelligent systems to support pre-frail people at home. | |
| Development of deep neural networks, based on convolutional layers, to classify images belonging to sub-sets of a given domain: opening the network to analyze the formed structure and tackling the problem of the “open set”. | |
| Music and rehabilitation: development of models that describe music understanding and possible role in the amelioration of symptoms in autistic spectrum disorders. | |
| Data Science methods and techniques for retrieval, integration, and exploration of heterogeneous data | |
| Semantic Language Product Lines and Multi-Dimensional Variability Models | |
| Code Feature Classification for Software Product Lines Automatic Generation by Using Machine Learning Techniques | |
| Algorithms for Online Process Mining | |
| Design and analysis of learning algorithms with partial feedbacks
Requisiti: Analysis of algorithms, probability and statistics, combinatorics, linear algebra |
|
| Design and analysis of multi-task learning algorithms
Requisiti: Analysis of algorithms, probability and statistics, combinatorics, linear algebra |
|
| Data driven mathematical programming: the research proposal targets the development of methodologies to integrate mathematical programming and machine learning.
Requisiti: Mathematical programming, statistics, machine learning, design and analysis of algorithms |
|
| Large Scale Prescriptive Analytics: design of methodologies for solving complex optimization problems in real world contexts where large size, dynamic, heterogeneous data make classical techniques unsuitable.
Requisiti: Mathematical modeling, operations research, statistics, simulation, design and experimental analysis of algorithms. |
|
| Formalization and analysis of systems and applications based on blockchainations | |
| Approximate logic synthesis for multilevel circuits | |
| Circuit synthesis for emerging technologies | |
| Combinatorial Optimization algorithms for complex decision problems
Requisiti: Foundations of Operations Research, Algorithms and Data Structures, C programming |
|
| Multiagent modelling and simulation of multilayer networks for social contagion, knowledge/innovation diffusion, cybersecurity | |
| Models and techniques for Artificial Intelligence as a Service.
Requisiti: Knowledge of the main machine learning and artificial intelligence techniques._x000D_ Knowledge of the main tools for Big Data analytics. |
|
| AI and mobility data analysis
Requisiti: Strong programming skills |
|
| Data security and privacy in emerging scenarios | |
| Multi-modal biometrics and multi-sensor fusion | |
| Less-constrained biometrics | |
| Controlled and collaborative query execution in distributed systems | |
| Musical features recognition from scores and audio signals | |
| Automatic adaptation of video game features based on the emotional response of players
Requisiti: Good programming skills. Knowledge of Video Game develotment techniques. Skills in Affective Computing and Signal Processing fields could be an added value |
|
| Decentralized Social Networks | |
| Big Data Modeling and Analytics
Requisiti: Skills in Probabilistic Modeling and Data Analytics. |
|
| Computational intelligence and applications
Requisiti: Skills in Probabilistic Modeling and Data Analytics. |
|
| Use of compiler techniques to secure code in Java environment (e.g, Android) against unstrusted unserialized data attacks
Requisiti: Solid background in system security an on the following computer science subjects: programming languages, computer architecture, Operating system and networking. |
|
| Design of new Malware Analyzer for Android environment by using HW security features such PT-Intel and SGX technology contro l'evasion.
Requisiti: Solid Background in System Security. Knowledge in Operating System, Computer Architecture, Computer Networking |
|
| Computer-based technologies for music education
Requisiti: Basic knowledge in Computer Science (programming languages, databases, etc.) and Music (music theory, fundamentals of harmony) |
|
| Induction of fuzzy sets through machine learning techniques
Requisiti: Machine learning, probability and statistics, computer programming |
|
| Compression of deep neural networks
Requisiti: Machine learning, computer programming |
|
| Distributed rendering techniques for large-scale multi-user virtual environments. | |
| Challenges in streaming entertainment applications. | |
| Assistive technologies on mobile devices | |
| Definition of Facilities for Supporting the Development of Cross-Domain IoT Applications | |
| The adoption of functional programming languages with dependant types (Coq, Agda, Idris, Liquid Haskell, F*) for certified programming, interactive theorem proving and property-based testing with applications to the meta-theory of programming languages
Requisiti: Functional programming, logic 101 |
|
| Learning informatics and computational thinking in primary and secondary school | |
| Data-Science Models and Techniques for the Digital Humanities and the History of Science
Requisiti: Fluent English. Solid background in computer science, with particular focus on machine learning and data management. |
|
| Learning the distribution of acoustic events in evolving environments
Requisiti: Digital signal processing, machine learning, python, matlab |
|
| Automatic classification and annotation of musical content
Requisiti: Digital signal processing, machine learning, python, matlab |
|
| Distributed algorithms for swarms of robots
Requisiti: Deep knowledge of theory of algorithms and theoretical computer science |
|
| Formal systems and complexity. The investigation concerns computational models and their behaviors (usually described in terms of formal languages), the relationships and simulations between different models and formalism, the related complexity aspects.
Requisiti: Theoretical computer science, formal languages |
|
| Dependable Cloud and Fog 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 | |
| Formal methods for Security- and Safety-critical Systems | |
| Rigorous Development Process for Software Engineering | |
| Procedural generation for story-driven video games based on playstyle and mood of players
Requisiti: Video game design, storytelling for video games |
|
| Automatic generation of contents for video games based on players’ preferences
Requisiti: Background in video game design and in AI for video games |
|
| Innovative techniques for medical imaging based on human visual perception | |
| Innovative techniques for the control of color appearance in the field of cosmetics | |
| Resources orchestration in Mobile Edge Computing
Requisiti: Mobile networks, mobile edge computing |
|
| Data protection techniques for the digital data market | |
| Deep learning: learning techniques and explainability | |
| Ambient intelligence: data analysis and machne learning for self-adaptive environments | |
| Representaions and processing of 3D digital models for real-time rendering
Requisiti: Computer Graphics |
|
| Computational fabrication: computer graphics and geometry processing tools for digital fabrication
Requisiti: Computer Graphics |
|
| Machine learning-based prediction of regulatory regions in the human genome
Requisiti: Background in Machine Learning and Bioinformatics |
|
| Computational graph-based methods for the Network Medicine
Requisiti: Background in Bioinformatics |
|
| Machine learning algorithms in Bioinformatics
Requisiti: Background knowledge about machine learning |
|
| High-speed cryptography: designing and implementing fast cryptographic software in order to speed up encryption/decryption functions.
Requisiti: Background knowledge: cryptography or algebra |
Courses list
January
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Data Security and Privacy in Emerging Scenarios | 2 | 10 | English | |
| Machine Learning methods for the Genome-wide detection of deleterious or pathogenic genetic variants | 2 | 10 | English | |
| Regression Test Selection and Prioritization | 3 | 16 | English | |
February
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Architectural patterns to deploy machine learning scalable applications | 4 | 20 | English | |
| Deep learning. Theoretical introduction and its application for face detection, recognition and camuflage. | 3 | 15 | English | |
| Governance, Risk and Compliance in Distributed Architectures | 2 | 10 | English | |
| Image processing: Demosaicking | 4 | 20 | English | |
May
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Network design (modeling, analysis and optimization of networks part 2) | 2 | 10 | English | |
June
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Quantum Computing: Theory, Models and Methods | 3 | 20 | English | |
July
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Geometry Processing Introductory Course | 2 | 10 | English | |
November
| Courses or activities | Professor(s) | ECTS | Total hours | Language |
|---|---|---|---|---|
| Optional | ||||
| Bionics and computational intelligence | 2 | 10 | English | |
| Data Lakes in Big Data Architectures | 2 | 10 | English | |
| Matheuristics for Combinatorial Optimization problems (Module 1) | 2 | 10 | Italian | |
| Matheuristics for Combinatorial Optimization problems (Module 2) | 2 | 10 | Italian | |
Following the programme of study
Contacts
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