Introduction

About the school

Italian Computer Science PhD granting institutions under the auspices of GRIN, organizes an annual school offering three graduate-level courses aimed at first-year PhD students in Computer Science. In addition to introducing students to timely research topics, the school is meant to promote acquaintance and collaboration among young European researchers. The 2018 edition of the School is the 24th in the series.
The school will offer 3 courses each consisting of 13 hours of lectures:

  • Provable security for low level execution platforms
    Prof. Mads Dam - KTH (Sweden)
  • Distributed models, MapReduce and large scale algorithms
    Dr. Silvio Lattanzi - Google Inc (Zurich, Switzerland)
  • Elements of Quantum Computation
    Dr. Herbert Wiklicky, Imperial College London (U.K.)

A final evaluation for each course is possible through a final exam or project as determined by the instructor. The daily schedule admits laboratory and/or working group activities to be organized in addition to the lectures.
The registration fee for the School is 550.00 Euro and includes all local expenses from the evening of 11 March to 16 March afternoon including all meals and on-site lodging in double-occupancy rooms. A reduced registration fee of 300.00 Euro is available for local students which will not use the on-site lodging facilities (it includes local expenses for the lectures, coffee breaks and lunches). It is possible to require one additional night for the students that want to leave on Saturday the 17th. In this case the additional cost is 50 Euros.
Attendance is limited to 50 students and will be allocated on a first-come-first-served basis.

Courses

Provable security for low level execution platforms

Prof. Mads Dam, KTH 

Abstract: Much attention has been paid in the recent years to the problem of verification for various types of low level execution platforms such as OS kernels, device drivers, hypervisors, and cryptographic software. In the course we cover a range of topics related to this problem: Formulating correct and relevant verification goals, formally modelling the hardware platforms and security requirements, and formally verifying that the requirements are met. We start in a rather idealised setting suitable for very simple hardware platforms such as those found in legacy embedded control systems, and gradually add system features such as virtual memory, devices and IO, and caches, and examine how the formalisations and verification approaches are adapted. The course presupposes familiarity with first order logic, the use of first order logic for modelling of computer systems, transition system semantics, and, preferably also some basic familiarity with processor architecture. At the end of the course the student should be able to independently model a piece of simple sequential system software and verify it at the level of transition system semantics against a high level behavioural specification.

Slides: Link

Distributed models, MapReduce and large scale algorithms

Dr. Silvio Lattanzi, Google Inc.

Abstract: As a fundamental tool in modeling and analyzing real world data, large-scale algorithms are a central part of any tool set for big data analysis. Processing datasets with hundreds of billions of entries is only possible via developing distributed algorithms under distributed frameworks such as MapReduce, Pregel, Gigraph, and alike. For these distributed algorithms to work well in practice, we need to take into account several metrics such as the number of rounds of computation and the communication complexity of each round. For example, given the popularity and ease-of-use of MapReduce framework, developing practical algorithms with good theoretical guarantees for basic algorithmic primitives is a problem of great importance.
In this course, we discuss how to design and implement algorithms based on traditional MapReduce architecture. In this regard, we discuss various basic algorithmic problems such as computing connected components, maximum matching, MST, counting triangle, clustering, diversity maximization and so on so for. In particular, we discuss a computation model for MapReduce and describe the sampling&filtering, local random walk, and core-set techniques to develop efficient algorithms in this framework.

Slides: Link

Elements of Quantum Computation

Dr. Herbert Wiklicky, Imperial College London

Abstract: This course aims to introduce the basic notions of quantum computing with particular emphasis on quantum algorithms. We will discuss basic quantum physical concepts - like Observable, State and Measurement - as well as central aspects of Quantum Computing - including Quantum Bits (qubits) and registers, Quantum Evolution, Quantum Circuits, Quantum Teleportation and the basic Quantum Algorithms known at the present time.
The lectures will cover: Introduction to Quantum Mechanics, Quantum Bits and Complex Vector Spaces, Quantum Evolution and Quantum Gates, Quantum Registers, No-Cloning Theorem, Quantum Key Distribution/Cryptography, Quantum Entanglement and Teleportation, Quantum Algorithms and Circuits, Quantum Search (Grover's Algorithm), Quantum Fourier Transform, Quantum Factoring of Integers (Shor's Algorithm); and possibly: further Quantum Algorithms, alternative Quantum Computing Models, Quantum Error Correction.
As pre-requisites we will assume a basic knowledge of basic Linear Algebra (i.e. vectors, matrices, basis, inner product, etc.)

Monographs:
  • Noson S. Yanofsky, Mirco A. Mannucci: Quantum Computing for Computer Scientists, Cambridge University Press, 2008
  • Eleanor Rieffel, Wolfgang Polak: Quantum Computing, A Gentle Introduction. MIT Press, 2014
  • Richard J. Lipton, Kenneth W. Regan: Quantum Algorithms via Linear Algebra. MIT Press, 2014
  • Phillip Kaye, Raymond Laflamme, Michael Mosca: An Introduction to Quantum Computing, Oxford University Press 2007
Electronic Introductions:
  • N.S.Yanofsky: An Introduction to Quantum Computing http://arxiv.org/abs/0708.0261
  • E.Rieffel, W.Polak: An introduction to quantum computing for non-physicists. ACM Computing Surveys, 2000 doi:10.1145/367701.367709

Slides: Link

Programmes


Provable security for low level execution platforms (PSP)
Distributed models, MapReduce and large scale algorithms (DML)
Elements of Quantum Computation (EQC)

2018
11/03
12/03
13/03
14/03
15/03
16/03
Sun
Mon
Tue
Wed
Thu
Fri
08.00-09.00
breakfast
09.00-10.00 DML DML DML PSP PSP
10.00-11.00 DML DML DML PSP PSP
11.00-11.30 coffee break
11.30-12.30 DML DML DML EQC PSP
12.30-13.30 DML DML DML EQC PSP
13.30-15.00 lunch
15.00-16.00 EQC PSP EQC PSP -
16.00-17.00 EQC PSP EQC PSP -
17.00-17.30 tea break
17.30-18.30 arrival EQC EQC PSP EQC -
18.30-19.30 EQC EQC PSP EQC departure

ORGANIZATION

Scientific Organizing Committee


Nicolò Cesa Bianchi, University of Milano
Pierpaolo Degano, University of Pisa
Maurizio Gabbrielli, University of Bologna

Local Organization


Andrea Bandini, CeUB
Monica Michelacci, CeUB
Michela Schiavi, CeUB
Tong Liu, University of Bologna, Italy

Registration

The registration fee for the School is 550.00 Euro and includes all local expenses from the evening of 11 March to 16 March afternoon including all meals and on-site lodging in double-occupancy rooms. A reduced registration fee of 300.00 Euro is available for local students which will not use the on-site lodging facilities (it includes local expenses for the lectures, coffee breaks and lunches). It is possible to require one additional night for the students that want to leave on Saturday the 17th. In this case the additional cost is 50 Euro. Attendance is limited to 50 students and will be allocated on a first-come-first-served basis.

In order to register, all applicants must fill the form available at the following link: REGISTRATION FORM.

Venue

BISS 2018 events are held in the University Residential Center located in the small medieval hilltop town of Bertinoro. This town is in Emilia Romagna about 50km east of Bologna at an elevation of 230m above sea level. View More

Via Frangipane, 6 in Bertinoro, Italy

+39 0543 446500

segreteria@ceub.it

http://www.ceub.it

Past Editions

BISS 2019:

  • TBD
  • TBD
  • TBD

BISS 2018:

  • Provable security for low level execution platforms
  • Distributed models, MapReduce and large scale algorithms
  • Elements of Quantum Computation

BISS 2017:

  • Approximation Algorithms
  • Probabilistic Graphical Models in Intelligent Systems
  • Kleene algebra with tests and applications to network programming

BISS 2016:

  • ADVANCED TOPICS IN PROGRAMMING LANGUAGES
  • MODELS AND LANGUAGES FOR SERVICE-ORIENTED AND CLOUD COMPUTING
  • ALGORITHMIC METHODS FOR MINING LARGE GRAPHS

BISS 2015:

  • Game Theory: Models, Numerical Methods, and Applications
  • Protection of sensitive information
  • Introduction to Modern Cryptography

BISS 2014:

  • Big Data Analysis of Patterns in Media Content
  • An Introduction to Probabilistic and Quantum Programming
  • Development of dynamically evolving and self-adaptive software

BISS 2013:

  • Foundations of Security: Cryptography, Protocols, Trust
  • Stochastic Process Algebras for Quantitative Analysis
  • Shape and Visual Apperance Acquisition for Photo-realistic Visualization

BISS 2012:

  • Algorithms for the web and for social networks
  • Software Verification and Interactive Theorem Proving
  • Regularization methods for high dimensional learning

BISS 2011:

  • Computational Aspects of Game Theory
  • Trust in Anonymity Networks (TAN)
  • Information Integration (II)
  • Model Checking: From Finite-state to Infinite-state Systems (MCFIS)