Scientific lectures and colloquia

The Faculty of Informatics regularly invites distinguished foreign and domestic scientists to give plenary lectures at the weekly Informatics Colloquium (with a tradition dating back to 1997) and on additional important occasions.
The lectures are usually given at the Faculty of Informatics, in lecture room D2, unless specified otherwise. See also the FI building tour.

Since the year 2018, moreover, Masaryk University has launched a new distinguished Seminar Series in Mathematics, Physics and Computer Science. This series brings to our university world top scientific speakers, selected and invited jointly by the Faculty of Informatics and the Faculty of Science. Lectures of the Seminar Series are given at the Mendel Museum in Brno.

2019

  •   18. 12. 2019, 16:30, Mendel Museum, Refectory of Augustinian Abbey (Mendlovo nám. 1a, Brno)

    Prof. Noga Alon

    Professor of Mathematics at Princeton University and Baumritter Professor Emeritus of Mathematics and Computer Science at Tel Aviv University

    Lecture Description

    The list chromatic number of a graph G is the minimum k so that for every assignment of a list of k colors to any vertex of G there is a vertex coloring assigning to each vertex a color from its list so that adjacent vertices get distinct colors. This notion was introduced by Vizing and by Erdős, Rubin and Taylor in the late 70s and its study combines combinatorial, probabilistic and algebraic techniques. Its natural extension to hypergraphs is closely related to questions in Euclidean Ramsey Theory. I will discuss several old and new problems and results in the area focusing on a recent work with Briceno, Chandgotia, Magazinov and Spinka motivated by questions in statistical physics regarding vertex colorings of the d-dimensional lattice.

    MU Seminar Series
  •   27. 11. 2019, 16:30, Governor's Palace, Baroque Hall (Moravské náměstí 1a, Brno)

    Prof. Martin Grohe

    Chair in Logic and the Theory of Discrete Systems, RWTH Aachen University, Germany
    ACM Fellow since 2018

    Lecture Description

    Symmetry is a fundamental concept in mathematics, the sciences, and beyond. Understanding symmetries is often crucial for understanding structures. In computer science, we are mainly interested in the symmetries of combinatorial structures. Computing the symmetries of such a structure is essentially the same as deciding whether two structures are the same ("isomorphic"). Algorithmically, this is a difficult task that has received a lot of attention since the early days of computing. It is a major open problem in theoretical computer science to determine the precise computational complexity of this "Graph Isomorphism Problem".
    One of the earliest applications of isomorphism testing was in chemistry, more precisely chemical information systems. Today, applications of isomorphism testing and symmetry detection are ubiquitous in computing. Prominent examples appear in optimisation, malware detection, and machine learning. However, in many of these applications, we only need to decide if two structures are sufficiently similar, rather than exactly the same. It turns out that determining how similar two structures are is an even harder computational problem than deciding whether they are isomorphic. My talk will be an introduction to algorithmic aspects of symmetry and similarity, ranging from the fundamental complexity theoretic "Graph Isomorphism Problem" to applications in optimisation and machine learning.

    MU Seminar Series
  •   6. 11. 2019, 16:30, Mendel Museum, Refectory of Augustinian Abbey (Mendlovo nám. 1a, Brno)

    Prof. Andreas Thom

    Professor of Geometry, TU Dresden, Germany

    Lecture Description

    I will discuss the concept of stability in mathematics. If a set of equations is almost satisfied, is it true that a true solution to the equations exists nearby? For example, if two permutations of X commute on most of the points of X, are there permutations of X that agree with the given permutations on most of the points and do commute? If a function on a Banach space is almost linear, is it close to a linear map? These type of questions and some positive answers were first discussed by Stanislaw Ulam in 1940 und the name of „stability“ and come up naturally in a variety of situations ranging from functional analysis, group theory, to computer science. I will explain the background and discuss some recent progress in a variety of circumstances.

    MU Seminar Series
  •   9. 10. 2019, 16:30, Mendel Museum, Refectory of Augustinian Abbey (Mendlovo nám. 1a, Brno)

    Prof. Dana Stewart Scott

    Emeritus Hillman University Professor of Computer Science, Philosophy, and Mathematical Logic at Carnegie Mellon University
    Holder of the ACM Turing Award 1976

    Lecture Description

    For a long time it has been known that enumeration operators on the the powerset of the integers form a model of the λ-calculus. More recently, the speaker realized that well-known methods allow for the adjunction of random variables to the model. Also other well-known ideas can expend the basic model into a model for Martin-Löf type theory. Some recent work with a group of collaborators combines the two approaches by invoking Boolean-valued models. The talk will address the question of how to give this natural modeling interesting applications.

    MU Seminar Series
  •   24. 9. 2019, 14:00, D2

    RNDr. David Šafránek, Ph.D.

    FI MU

    Computer-Aided Systems Biology

    Lecture Description

    In this lecture, we will introduce a novel paradigm for solving problems in biology. First, we will describe the framework of systems biology. Second, we will present an original approach to systems biology implemented on fundamental principles developed in computer science. Part of the talk will be dedicated to the comprehensive modelling platform we are developing in our research.

    Public talk within a Habilitation procedure

  •   23. 4. 2019, 14:00, D2

    RNDr. Vojtěch Řehák, Ph.D.

    FI MU

    What is the best timeout?

    Lecture Description

    We all have some experience with deadlines, and we know how hard it is to deliver results in time, especially when some obstacles with an uncertain solving time may occur. In this talk, we deal with formalisms suitable for modeling and analysis of such systems, i.e., reflecting both timeouts and actions taking stochastic continuous time. We show how this kind of stochastic timed systems can be modeled and what properties can be computed for such models. On surprisingly small examples we also demonstrate some fundamental limits of such models. Then we will consider that some parts of the model are unknown and we take them as parameters that we would like to synthesize automatically. Finally, we will present results allowing for the synthesis of (epsilon)-optimal timeouts in such systems

    Public talk within a Habilitation procedure

  •   16. 4. 2019, 14:00, D2

    Dr.rer.nat. RNDr. Mgr. Bc. Jan Křetínský, Ph.D.

    Technical University of Munich

    Machine learning in verification

    Lecture Description

    On the one hand, formal verification methods provide hard guarantees on analysis results, but do not scale well and are often hard to use. On the other hand, machine learning comes with weak or no guarantees, but scales well and can provide more understandable solutions. In this talk, we show several examples how these approaches can be combined and the best of the two worlds achieved. We demonstrate this on controller synthesis and controller representation in the setting of Markov decision processes and games.

    Public talk within a Habilitation procedure

  •   26. 3. 2019, 14:00, D2

    RNDr. Petr Švenda, Ph.D.

    FI MU

    Analysis and use of RSA keypair generation bias

    Lecture Description

    Analysis and use of RSA keypair generation bias The talk will explain the details of recently discovered bias in RSA keys produced by various cryptographic libraries. The bias allows to attribute RSA public key to its origin library and already lead to results with practical security impact: 1) A discovery of factorable keys from smartcards (so-called ROCA vulnerability), 2) a revelation of cryptographic keys supposedly generated on-chip while actually generated outside and only later injected and 3) a first direct measurement of cryptographic smartcard popularity in Internet-wide datasets. The reason for the bias presence steaming from the prime generation algorithms will be explained with typical usage scenarios for accurate key origin attribution. The talk will also cover ongoing research and open research directions.

    Public talk within a Habilitation procedure

  •   19. 3. 2019, 14:00, D2

    RNDr. Radek Ošlejšek, Ph.D.

    FI MU

    Semantic data modeling – conceptual view

    Lecture Description

    In this talk, I will explain the principles of semantic modeling. I will briefly compare popular data models, such as rational vs. NoSQL databases. Then, I will focus on graph ontologies. I will describe their features, the problem of abstraction, information levels (e.g., upper vs. domain ontologies), and other aspects that are important for semantic modeling. The discussion will be supported by practical examples that emerged in our research of the semantic modeling of image content. Examples from the cybersecurity domain will, in turn, demonstrate the abilities and limitations of ontologies for detection and mitigation of cyber threats. Possible utilization of ontologies for formal knowledge modeling in hands-on cybersecurity training will be presented as well.

    Public talk within a Habilitation procedure

2018

  •   9. 11. 2018, 9:00, Mendel Museum, Refectory of Augustinian Abbey (Mendlovo nám. 1a, Brno)

    Prof. Anuj Dawar

    Professor of Logic and Algorithms at the University of Cambridge
    Fellow of the Alan Turing Institute in London

    The Limits of Symmetric Computation

    Lecture Description

    The most famous open problem in theoretical computer science, known as the P vs. NP problem challenges us to prove that for some natural search problems, no efficient algorithm is possible. At the moment, we have no idea how to prove such a statement. In order to make meaningful progress, we can restrict the class of algorithms we consider and show that, within these restrictions, no efficient algorithm exists. In this talk, I consider a natural restriction to symmetric algorithms. I explain how symmetries arise naturally in computational problems and why algorithms that respect these symmetries have inherent limitations. Many of our most powerful algorithmic techniques are symmetry-preserving, while others are not. Exploring these limits offers a rich research agenda combining logic, algebra and combinatorics with algorithms.

    MU Seminar Series
  •   10. 10. 2018, 16:00, Mendel Museum, Refectory of Augustinian Abbey (Mendlovo nám. 1a, Brno)

    Prof. Javier Esparza

    Faculty of Computer Science, Technische Universität München, Germany.

    Black Ninjas in the Dark: Analyzing Population Protocols

    Lecture Description

    Population protocols are a mathematical model of distributed computation introduced by Angluin et al. in 2004. The original purpose of Angluin et al. was the theoretical study of systems consisting of identical, cheap mobile devices with tiny computational resources, like sensor networks. However, since its introduction the model has also been used to analyze the behaviour of chemical systems and of people in social networks. Population protocols help us to pose and study many fundamental questions about distributed systems: What can be computed by agents wishing to remain anonymous? Are leader processes necessary for optimal speed? Can macroscopic "phase transitions" be "programmed" at microscopic level? Is it possible to check automatically that a protocol works correctly? Is it possible to automatically synthesize a protocol for a given task? In the talk I will introduce the population protocol model with the help of several examples. More precisely, I will present the problem of the Black Ninjas in the Dark, and the different solutions given to it by their Senseis. I will also show animated simulations of some protocols.

    MU Seminar Series
  •   22. 5. 2018, 14:00, D2

    Mouzhi Ge, Ph.D.

    FI MU

    Recommender System Research in E-Commerce

    Lecture Description

    Over the last decade, recommender systems have been widely applied in e-commerce, for example, video recommendations in Youtube, book recommendation on Amazon, and movie recommendation on Netflix. Recommender systems are developed to help users find relevant products that may interest them. The goal of recommender systems is to reduce the information overload and provide personalized recommendations for users. In this talk, I will discuss the state-of-the-art research of recommender system in E-Commerce, which includes rationale and algorithms inside the recommender black box, important features and evaluations in recommender systems. Finally, a real-world food recommender system project in E-Commerce will be described and demonstrated to show how to construct and evaluate the recommender system in practice, as well as possible challenges that are related to the food recommender systems.

    Public talk within a Habilitation procedure

  •   27. 3. 2018, 14:00, D2

    Ing. Vlad Popovici, M.Sc., Ph.D.

    Faculty of Science MU

    Case studies in multimodal biomarker discovery

    Lecture Description

    High throughput genomic revolution started almost twenty years ago with the first in-house printed DNA chips. Since then, various technologies evolved, allowing the interrogation of the whole (human) genome, proteome, metabolome, etc., all producing large amounts of data. Bioinformatics tools and methods evolved to account for all these data modalities with the current bottleneck being the integration of these perspectives into a more comprehensive picture. In parallel and completely independent of bioinformatics, digital pathology also witnessed significant advances fuelled mostly by technological developments: slide scanners and computational infrastructure. However, both “classical” bioinformatics and digital pathology/bioimaging are often used to investigate the same biological phenomenon. It is, therefore, natural to attempt to combine these two seemingly incompatible fields with the hope of unveiling new connections between them. In this talk we will look at three examples of jointly mining the transcriptome and the histopathology images in the context of breast and colon cancers. We will also discuss the computational challenges one faces when working with these data.

    Public talk within a Habilitation procedure

  •   16. 2. 2018, 11:00, D3

    Prof. Daniel Kráľ

    University of Warwick, UK

    Models of Large Networks

    Lecture Description

    A graph is a mathematical model of a network of nodes, which can be, e.g., a computer network or a social network. Problems concerning networks of enormous sizes, which more and more often arise in computer science applications, led to a need to find new mathematical tools to represent and analyze large graphs. The theory of graph limits, whose foundations were laid at Microsoft Research about a decade ago, has responded to these challenges by developing analytic models of large graphs.

    We will provide a brief self-contained introduction to the theory of graph limits, which will be followed by the exposition of the most major lines of research. We will conclude with presenting solutions of some of the most significant open problems in the area.

Past lectures

2017

  •   10. 11. 2017, 9:00, Mendel Museum, Refectory of Augustinian Abbey (Mendlovo nám. 1a, Brno)

    Prof. Juraj Hromkovič

    Department of Computer Science, ETH Zurich

    Teaching mathematics and computer science as research instruments

    Lecture Description

    We view mathematics as a language that was and is developed in order to describe what is describable in an unambiguous way (everybody mastering this language interprets each sentence in the same way) and in order to have a language in which the correctness of each argumentation is verifiable. Together with experiments mathematics became the main research instrument for discovering our world. In this talk we present the history of the development of mathematics and computer science in a concise way and recognize that the main contributions of science are not in discovering facts, but in introducing new concepts that increase the power of our research instruments. Finally, we discuss why and how we have to change our education in mathematics and science that is still living in a more than 100 years old world of technical revolution. The main idea is based on moving from teaching long time optimized and finalized products of scientific work as facts, relationships and methods to teaching the processes of the development of research instruments and of making discoveries. The main goal is to force the intellectual growth of young people, to motivate them to strive to understand and to be creative.

    MU Seminar Series

  •   3. 10. 2017, 14:00, D2

    Mgr. Jan Obdržálek, Ph.D.

    FI MU

    Digraph Width Measures

    Lecture Description

    Treewidth, defined by Robertson and Seymour, proved to be an extremely successful graph parameter. Intuitively, it measures how much tree-like a given graph is. Many problems which are NP-hard on general graphs become tractable on graphs of low treewidth. However treewidth quickly hits its limits once we try to apply it to directed graphs. Directed acyclic graphs (DAGs), on which many problems have simple efficient algorithms, can have arbitrarily high treewidth. Naturally one can ask whether there is a digraph width measure with all the nice properties of treewidth. In this talk we first quickly survey some of the known digraph width measures, and then try to answer the question whether there indeed is a good directed counterpart to treewidth.

    Public talk within a Habilitation procedure

  •   2. 5. 2017, 14:00, D2

    Ing. RNDr. Barbora Bühnová, Ph.D.

    FI MU

    Quality-Driven Software Architecture Design

    Lecture Description

    Software architecture design is one of the key activities in any software engineering process. The decisions made during software architecture design have significant implications for economic and quality goals related to the developed software product. To better guide the software architect along the design process and prevent an evaluation of an enormous number of design alternatives, various architectural tactics have been introduced. Generally, these tactics are designed to improve a specific quality attribute, but often declare an additional cost in terms of degrading the architecture with respect to other quality attributes. It is the task of the software architect to evaluate various solutions and determine a good trade-off between all existing quality and cost goals. In this lecture, we discuss the concepts that make up the field of quality-driven software architecture design. We will focus on the basics, best practices, as well as the challenges that are currently studied by the research community.

    Public talk within a Habilitation procedure