Programme and courses

The programme lasts three years and is taught in English. Each student will have to attend and pass the test of at least four courses of 30 hours each (or equivalent solutions) in the first 18 months for a total of 120 hours of teaching activities, the remaining 18 months being entirely devoted to the research project.

Class timetable

Discover the timetables of the classes, workshops and other learning activities of the Phd programme in Computer science.

For the academic year 2018/2019 courses offered are as follows:

Mandatory

Advances in Autonomous, Distributed and Pervasive Systems (30 hrs)

Lecturers: prof. Riccardo Focardi, prof. Andrea Marin, dr. Claudio Silvestri, dr. Stefano Calzavara

Venue: Ca' Foscari Scientific Campus - via Torino, Mestre

Date and time: detailed information will follow soon

Syllabus:

  • Part 1 (prof. Riccardo Focardi)
    Security APIs (4 hours)Security mechanisms usually offer to programmers APIs that allows for managing sensitive data and cryptographic keys. We will revise the security of these APIs focussing on two practical case studies.
    Breaking and fixing Java keystores (3 hours)Cryptographic keys are stored into encrypted keystore files. We will introduce the principles behind keystore security and show recent vulnerabilities (and relative fixes) we found in Java keystores.
    Semantic-based firewalling (3 hours)Configuring firewalls is complex and error-prone. We will revise a recent language that allows for analysing and configuring firewalls focussing on the firewall security policy (i.e. the firewall semantics).
    Date and time:

    • 12/03, 14.30-16.45 Meeting Room B 
    • 13/03: 10.30-12.45
    • 14/03: 12.00-13.30
    • 15/03: 10.30-12.00

    All lectures will be held in the Acadia Lab

  • part 2 (prof. Andrea Marin, dr. Claudio Silvestri)
    The course will also address the problem of content allocation in data intensive applications.
    In a first part, theoretical models and protocols for load balancing and high performance will be addressed thanks to an introduction to queueing theory and the optimality of the allocation protocols. This part will be followed by a laboratory part in which real case studies will be shown. More specifically, the topics addressed by the course will be:

    • introduction to stochastic modeling
    • queueing theory and fundamental queues
    • optimality of the scheduling and the Shortest-Remaining-Processing-<wbr />Time discipline
    • optimality of the resource allocation policies: comparison between round robin, join the shortest queue, and other disciplines
    • tools for handling high volumes of messages: zeroMQ, RabbitMQ, Apache Flume, Apache Kafka, Apache Samza, Apache Spark Streaming 

    Date and time: 

    • 07/03, 14-15.30 Meeting Room B
    • 08/03, 14-15.30 and 15.45-17.15 Acadia Lab
    • 11/03, 14-15.30  Acadia Lab
    • 15/03, 14-15.30  and 15.45-17.15  Acadia Lab

  • Part 3 (dr. Stefano Calzavara)
    Web session securityWe will study how authenticated access is implemented on the web by means of cookies and the security threats associated to this common practice.
    Adversarial machine learningWe will show that traditional machine learning techniques fall short against adversarial manipulations and discuss how they can be improved in this respect.
    Date and time:

    • 20/03, 15.30-17.45, Delta 1 B classroom
    • 21/03, 15.30-17.45, Meeting Room B (Zeta building)

KIIS Colloquia (30 hrs)

Lecturers: prof. Claudio Lucchese, prof. Marcello Pelillo, prof. Andrea Torsello

Venue: Ca' Foscari Scientific Campus - via Torino, Mestre

prof. Pelillo (10 hrs)

Date and time: tentative period, second semester (Spring 2019)
Class schedule will follow later on.

Syllabus: Philosophical Aspects of Machine Learning

Abstract
The field of machine learning can arguably be considered as a modern-day incarnation of an endeavor which has challenged mankind since antiquity. In fact, fundamental questions pertaining to categorization, abstraction, generalization, induction, etc., have been on the agenda of mainstream philosophy, under different names and guises, since its inception. With the advent of modern digital computers and the availability of huge amount of raw data, these questions have now taken a computational flavor. In recent years there has been a revival of interest around the foundational and/or philosophical problems of machine learning, from both the computer scientist's and the philosopher's camps. This suggests that the time is ripe to attempt establishing a long-term dialogue between the philosophy and the machine learning communities with a view to foster cross-fertilization of ideas. The goal of this tutorial is to provide a timely and coherent picture of the state of the art in the field and to stimulate a discussion and a debate within our community. This could be an opportunity for reflection, reassessment and eventually some synthesis, with the aim of providing the field a self-portrait of where it currently stands and where it is going as a whole. We shall assume no pre-existing knowledge of philosophy by the audience, thereby making the tutorial self-contained and understandable by a non-expert.

prof. Lucchese (10 hrs)

Date and time: tentative period, early June 2019Class schedule will follow later on.

Syllabus: Helping a user in finding interesting pieces of information among the billions pages of the Web is a very challenging problem, an open research area and an application field for the most advanced techniques in the areas of Web Search and Data Mining. This course reviews the most recent advances in the areas of Web Search and Data Mining. Topics include: Web Mining, Learning to Rank, Graph Mining and Social Network Analysis.

prof. Torsello (10 hrs)

Date and time: tentative period, June/July 2019
Class schedule will follow later on.

Syllabus: Intro to quantum computation
Abstractthis course will be composed of a series of open seminars introducing the fundamentals of quantum computing, quantum algorithms and quantum information theory.


Optional courses

Bertinoro School (first year students only)

Lecturers: local lecturers

Venue: http://www.cs.unibo.it/projects/biss2018/ 

Date and time: February/March 2019

Syllabus: see School website


Other courses (managed by Ca' Foscari PhD Office)

Students will have to attend at least 2 courses organized by PhD Office, language and computer science ones excluded. 
Students will have the possibility to apply for other Schools and courses (even held outside Ca' Foscari. Minimum required level: M.Sc. courses) by submitting their requests to PhD Coordinator/Board of Professors.

Last update: 19/03/2019