Once a week during the academic year, an invited speaker (from abroad, as well as from the Czech Republic) talks about his or her scientific work. Colloquium takes place at the Faculty of Informatics and is open to the scientific community. Lecture dates can be found in the programme. Tuesday 14.00 - 15.00, D2, FI MU, Botanická 68a

Colloquia programme with abstracts for the Autumn 2016 semester

20. 9. 2016
doc. PhDr. Karel Pala, CSc., FI MU
Verb valency frames and knowledge representation
Abstrakt: The talk will be devoted to the verb valency frames and their use for knowledge representation integrating syntactic and semantic structures of a natural language. The results obtained in this respect for Czech, particularly the lexical database VerbaLex, will be presented. This resource can be used in various NLP applications such as syntactic analysis, information extraction, machine translation.
27. 9. 2016
dr. Edgar Weippl, SBA Research, Vídeň
Applied Research in Information Security
Abstrakt: Applied research in network security is becoming increasingly important as many large scale cloud systems and complex decentralized networked systems are used today by millions of people. Often, the systems’ characteristics cannot be observed directly, either because the operators of centralized services do not provide this information (e.g. Facebook, Amazon) or because the decentralized nature does not allow doing so (e.g. crypto protocols used on servers, Tor). In addition, software development becomes more complex as software is developed in large, globally distributed teams so that one has to operate under the assumption that within any large team there are people trying to incorporate malicious code into the code base. Up to date there is little work that provides any empirical evidence on how widespread such problems are and whether there are effective means (and which) to mitigate this risk.Research methodology in information security is evolving and many of the earlier well- known empirical research findings are hard to reproduce for two main reasons: First, the original data is not or no longer available or may have been altered. Second, research ethics have changed and some experiments are no longer an acceptable practice.In this presentation I will (1) highlight the impact of our past research in the field, (2) show how promising theoretical concepts can be explored and applied to important empirical problems, and (3) explore future research paths in the field.
4. 10. 2016
Francesco Caputo, FI MU
The role of Service Logic and Systems Thinking in managing social and economic complexity
Abstrakt: In the last few years, an increasing numbers of social and economic events such as the globalization, the diffusion of new Information and Communication Technologies, and the changes in consumers and users’ lifestyles and habits have profoundly affected our daily lives. As consequences of all these events, traditional managerial models are showing an increasing useless in supporting policy and decision makers in defining efficient, effectiveness, and sustainable social and economic challenges.

In order to overcome the limitation of traditional reductionist approaches, the presentation will focus the attention on the contributions that the Service Logic and the Systems Thinking can offer in the definition of new more performant approaches for the management of increasing social and economic variety.

In such a line, the presentation will analyse the key concepts of a possible new interpretative framework in which knowledge, competences, and capabilities are the key drivers on which act in order to define a new perspective in the management of every kinds of organization.

11. 10. 2016
Dr. Mouzhi Ge, Faculty of Computer science, Free University of Bozen-Bolzano
Landscape of Recommender System Research
Abstrakt: Recommender system is to help users find relevant products that may interest them. Over the last decade, recommender systems have been widely devdeloped in many real-world applications such as book recommendations in Amazon, movie recommendations in Netflix, friend recommendations in Facebook, and video recommendations in Youtube. In this talk, I will discuss the state-of-the-art research in recommender systems, which includes rationale and algorithms behind the recommender black box, important features and evaluations in recommender systems, as well as recommender system research in different domains. This talk will be concluded by discussing the emerging research streams in recommender systems and possible interdisciplinary research with other research communities.
18. 10. 2016
Dr. Ivan Viola, Institute of Computer Graphics and Algorithms, Vienna University of Technology
Multi-Scale Molecular Data Visualization
Abstrakt: The study of biological processes carried out in living organisms is among the central foci of modern science. The field is nowadays by large extent computational, there are many kinds of digital models that characterize particular aspects of life. To provide a comprehensive view on biological phenomena, visualization offers itself for integrating multiple models into one visual environment.

One of the interesting challenges, associated with such a visual integration, is to communicate phenomena that are simultaneously described on several spatial and temporal scales. In my talk we will discuss a variety of visualization techniques that bridge several orders of magnitude of spatial scale by interactively rendering structural information from a single atom level (10−10 m) up to the scale of entire viruses or bacteria with a complete molecular machinery (ca. 10−6 m). Integrative structural biology models are very dense and consist of many structures each of these serving a particular function. In order to convey such information clearly, I will discuss how visual abstractions help us to visualize multiple scales and how these techniques can be used to deal with the structural occlusion inherent in the integrative model. To convey a living structure, large structural models can be extended with dynamic biological models of physiology. In the last part of my talk I will discuss an integration of molecular reaction pathways with the structure. The reactions are modelled quantitatively, can be executed in run-time during interactive visualization to allow for interactive visual steering of the simulation parameters.

25. 10. 2016
prof. Jens Rittscher, Institute for Biomedical Engineering, University of Oxford
Quantitative Methods for Cell and Tissue Imaging
Abstract: Building on recent advances in computer vision and machine learning we are now in the position to monitor complex biological environments and events in the same way are analysing natural scenes. While challenges remain, algorithms for cell segmentation and tracking have matured significantly and can now be used in more routine high-throughput settings. Improved microscopy and imaging platforms not only allow us to image subcellular events at high spatial and temporal resolution, we can now image large tissue sections and capture how various different proteins modulate the cellular microenvironment. Enabled by advances in cell culturing technologies 3D cultures can restore specific biochemical and morphological features that are similar to their in vivo counterparts. This holds the potential for improving relevance of in vitro studies, improving our ability to predict what occurs in vivo.

We are now working towards establishing the spatial and temporal context for biological events and processes. Quantitative image analysis methods are necessary for monitoring the tissue formation process and enabling longer duration time-lapse imaging. Quantitative imaging can be used very effectively to analyse the cell-to-cell and cell-to-matrix interactions that characterize the microenvironment as well as migration and invasion mechanisms. A more ambitious goal is the analysis of collective cell migration, which plays a crucial role in development and disease progression. The talk will provide examples on how quantitative imaging will advance our understanding of biological mechanisms. In addition the talk with show examples of applying similar methods to histology imaging.

Short biography: The research of Prof. Jens Rittscher is to enable biomedical imaging through the development of new algorithms and novel computational platforms. Current focus of his research is to improve mechanistic understanding of cancer and patient care through quantitative analysis of image data. In 2013 he has been appointed to the first joint academic appointment between the Department of Engineering Science and the Nuffield Department of Medicine at the University of Oxford, UK. He has been awarded the title of Professor of Engineering Science. He is a group leader at the Target Discovery Institute and is a member of the Ludwig Institute of Cancer Research.

Prior to coming to Oxford Jens Rittscher was a senior research scientist and manager at GE Global Research in Niskayuna (NY, USA), one of the world’s largest and most diversified industrial research laboratories. Building on his extensive expertise in computer vision, probabilistic modelling and statistical learning, he developed new theoretical approaches that address specific real-world challenge problems in automated video annotation, visual surveillance, and biomedical imaging. In the context of biomedical imaging he worked on applications ranging from monitoring cellular processes and computational pathology to the development of an anatomical atlas for zebrafish imaging. In addition he held a position as an adjunct professor at the Rensselear Polytechnic Institute in Troy (NY, USA).

1. 11. 2016
prof. RNDr. Václav Matyáš, M.Sc., Ph.D., RNDr. Petr Švenda, Ph.D., FI MU
The Million-Key Question – Investigating the Origins of RSA Public Keys
Abstrakt: Can bits of an RSA public key leak information about design and implementation choices such as the prime generation algorithm? We analysed over 60 million freshly generated key pairs from 22 open- and closed-source libraries and from 16 different smartcards, revealing significant leakage. The bias introduced by different choices is sufficiently large to classify a probable library or smartcard with high accuracy based only on the values of public keys. Such a classification can be used to decrease the anonymity set of users of anonymous mailers or operators of linked Tor hidden services, to quickly detect keys from the same vulnerable library or to verify a claim of use of secure hardware by a remote party. The classification of the key origins of more than 10 million RSA-based IPv4 TLS keys and 1.4 million PGP keys also provides an independent estimation of the libraries that are most commonly used to generate the keys found on the Internet. Our broad inspection also provides both sanity check and deep insight regarding which of the recommendations for RSA key pair generation are followed in practice, including closed-source libraries and smartcards.

The talk will be based on Usenix Security 2016 Symposium paper (that won the best paper award) and will also provide fresh details from our continuous analysis of more libraries and smartcards we perform after the conference itself.

8. 11. 2016
Doc. Mgr. Martin Nečaský, Ph.D., MFF UK
Linked Open Data: Current State and Future Trends
Abstrakt: Linked Open Data is a set of simple principles for publishing and accessing structured data on the Web. In this lecture, I will present these principles and show you the motivation for publishing data in this way. There are two interesting research challenges we will discuss in the lecture. First, it is how Linked Open Data should be discovered on the Web by users such as data journalists. Second, how the data published according to these principles should be processed by these users who are not familiar with technologies behind Linked Open Data (such as, e.g., RDF and SPARQL). I will present the state of the art in this area and also research activities of my research group. Besides these research topics, I would like to share with you also our activities in the area of Open Data. Because having Open Data is a necessary predecessor of having Linked Open Data. Therefore, I will walk you through our distressful journey from Open Data ideas to their implementation in Czech legislation.
15. 11. 2016
doc. RNDr. Tomáš Brázdil, Ph.D., FI MU
Deep Reinforcement Learning
Abstract: Deep reinforcement learning (DRL) is a machine learning method responsible for one of the latest breakthroughs in artificial intelligence demonstrated by human-level game playing capabilities. The method is based on combination of reinforcement learning and deep neural networks, where the networks, called deep Q-networks, learn successful policies directly from high-dimensional sensory inputs using reinforcement learning algorithms. I will start by introducing basic building blocks, namely I will shortly describe basics of Markov decision processes and learning neural networks. Subsequently, I will present some details of DRL in playing Atari games and comment on current trends in DRL.
22. 11. 2016
doc. PhDr. Karel Pala, CSc., RNDr. Vojtěch Kovář, Ph.D., FI MU
Punctuation Detection and Correction for Czech
Abstract: Punctuation detection belongs to important tasks in automatic checking of grammar, especially for the Czech language. However, it is one of the most difficult tasks as well, unlike e.g. correcting simple spelling errors. There are several automatic tools that partly solve the problem: Two commercial grammar checkers for Czech (which also try to correct other types of errors, but we will deal with their punctuation correction features only) and some academic projects, mainly focused on correcting punctuation. The lecture will introduce and thoroughly compare the available tools for this task, including our solution that outperforms the state-of-the-art tools in certain important aspects. We will discuss the accuracy results and the options for further development.
29. 11. 2016
RNDr. Radka Svobodová Vařeková, Ph.D., Výzkumná skupina Výpočetní chemie, Středoevropský technologický institut
Detection, Validation, Visualization and Characterization of Key Patterns in Molecular Data
Abstract: Biomacromolecular structural data is one of the most interesting and important results of modern life sciences. Key parts of this data are fragments (patterns) representing biologically important regions of biomacromolecules (active or binding sites, channels, secondary structure elements, etc.). The research of these patterns can provide ground breaking results in the fields of drug discovery, medicinal chemistry, environmental research, biotechnologies etc.. On the other hand, processing of biomacromolecular structural patterns is very challenging from informatics and algorithmic point of view. The talk will describe essential steps of biomacromolecular structural patterns research - their detection, validation, visualization, comparison and characterization. Specifically, we will focus on methodologies and algorithms used in these steps and their IT challenges. Afterwards, selected scientifically interesting results of this research will be shown: a quality comparison of different molecular classes, a structure-based prediction of molecular properties and a discovery of apoptosis (programmed cell death) mechanism.
6. 12. 2016
prof. Francesco Polese, University of Salerno
Systems Theories contributes to Service Science
Abstract: Service Science is a multicultural scientific domain addressing service systems, their desing, functioning, performance looking for the conditions and enablers of value co-creation in service exchanges. Service Systems are the focus of this research mainstream, indeed related to many other scientific domains such as that of big data analytics, management, engineering, legal sciences, marketing, human behavior, systems thinking. This latter, and in particular the Viable Systems Approach (VSA), supports the understanding of complex phenomena and with its theoretical suggestions, its postulates and fundamental concepts can be very useful to better understand service exchanges. A deepening of the VSA is hence most welcome in order to better manage decision making involving service systems, complex adaptive systems, complex service systems, smart service systems, smart cities and communities, and all topics interested by smarter planet initiative and by the service science community.

Short biography:

  • Born in Naples, 10th April 1970
  • Electrotechnical Engineer (1995)
  • Professor of Business Management (2005)
  • Director of InterDept. Simas (2013)
13. 12. 2016
prof. RNDr. Jaroslav Nešetřil, DrSc., MFF UK
Abstract: It is an old dream of mathematicians to replace the cumbersome investigation of particular cases by certain limit behaviour which would reflect the finite properties and hopefully would be simpler to handle. In the lecture we survey a particular recent activity which is both analytic and model theoretic and leads to a surprising connection to new techniques in clustering and modeling of sparsity.
20. 12. 2016
prof. Daniel Kráľ, Department of Computer Science, University of Warwick
Permutations - quasirandomness and property testing
Abstract: The theory of combinatorial limits offers analytic tools to represent and analyze large discrete objects. In the talk, we first present a self-contained introduction to the theory and we then focus on three applications concerning large permutations. The first is a characterization of quasirandom permutations by pattern densities, which resolves a question of Graham. The second is the permutation analogue of the result of Erdos, Lovasz and Spencer on the independance of densities of subgraphs. This result is then used in the third application, which concerns property and parameter testing algorithms, i.e., algorithms that provides a correct answer based on a small random sample of their input with high probability.