Computer science

Doctoral programme (PhD)
A.Y. 2019/2020
Study area
Science and Technology
Doctoral programme (PhD)
Dipartimento di Informatica "Giovanni degli Antoni" - Via Celoria, 18 - Milano
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.
Tutte le classi di laurea magistrale
Dipartimento di Informatica "Giovanni degli Antoni" - Via Celoria, 18 - Milano
Title Professor(s)
An assurance monitoring technique for the cloud based on big data analytics
Requirements: Cloud Architecture, basic notions of Big Data Pipelines, basic notions of Computer Security
Assurance Techniques for the Internet of Things.
Requirements: Knowledge of the main cloud and IoT technologies.
Development and validation of innovative music interfaces
Requirements: Audio and MIDI programming; Experimental methods in HCI
Sonic interaction design and assistive technologies for blind and visually impaired users
Requirements: Audio and MIDI programming; experimental methods in HCI
Advanced techniques for sound synthesis and 3D rendering in interactive contexts
Requirements: Digital signal processing, audio programming
Multi-level navigation in musical contents
AI techniques for sensor-based human activity recognition
Personal Data Protection in Smart Environments
Requirements: 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
Requirements: 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
Requirements: Analysis of algorithms, probability and statistics, combinatorics, linear algebra
Design and analysis of multi-task learning algorithms
Requirements: 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.
Requirements: 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.
Requirements: 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
Requirements: 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.
Requirements: 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
Requirements: 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
Requirements: 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
Requirements: Skills in Probabilistic Modeling and Data Analytics.
Computational intelligence and applications
Requirements: 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
Requirements: 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.
Requirements: Solid Background in System Security. Knowledge in Operating System, Computer Architecture, Computer Networking
Computer-based technologies for music education
Requirements: Basic knowledge in Computer Science (programming languages, databases, etc.) and Music (music theory, fundamentals of harmony)
Induction of fuzzy sets through machine learning techniques
Requirements: Machine learning, probability and statistics, computer programming
Compression of deep neural networks
Requirements: 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
Requirements: 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
Requirements: 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
Requirements: Digital signal processing, machine learning, python, matlab
Automatic classification and annotation of musical content
Requirements: Digital signal processing, machine learning, python, matlab
Distributed algorithms for swarms of robots
Requirements: 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.
Requirements: 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
Requirements: Video game design, storytelling for video games
Automatic generation of contents for video games based on players’ preferences
Requirements: 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
Requirements: 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
Requirements: Computer Graphics
Computational fabrication: computer graphics and geometry processing tools for digital fabrication
Requirements: Computer Graphics
Machine learning-based prediction of regulatory regions in the human genome
Requirements: Background in Machine Learning and Bioinformatics
Computational graph-based methods for the Network Medicine
Requirements: Background in Bioinformatics
Machine learning algorithms in Bioinformatics
Requirements: Background knowledge about machine learning
High-speed cryptography: designing and implementing fast cryptographic software in order to speed up encryption/decryption functions.
Requirements: Background knowledge: cryptography or algebra

Courses list

November 2019
Courses or activities Professor(s) ECTS Total hours Language
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
January 2020
Courses or activities Professor(s) ECTS Total hours Language
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 2020
Courses or activities Professor(s) ECTS Total hours Language
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
Image processing: Demosaicking 4 20 English
May 2020
Courses or activities Professor(s) ECTS Total hours Language
Network design (modeling, analysis and optimization of networks part 2) 2 10 English
June 2020
Courses or activities Professor(s) ECTS Total hours Language
Quantum Computing: Theory, Models and Methods 3 20 English
July 2020
Courses or activities Professor(s) ECTS Total hours Language
Geometry Processing Introductory Course 2 10 English