Colloquia programme with abstracts for the Spring 2018 semester
- 20. 2. 2018
- ao. Univ.-Prof. Dipl.-Ing. Dr. Renate Motschnig, Faculty of Computer Science, University of Vienna
- Transforming Communication in Leadership and Teamwork – Why should computer scientists care?
- Abstrakt: Numerous sources report that the major reason for ICT-project failure are people- rather than technical issues. Thus, in order to improve project success, the most evident thing to do seems to care about the human factor in ICT projects. This influential “soft”, “fuzzy”, and “complex” factor, however, has tended to be overlooked, such that a number of research gaps at the interface between software engineering and human sciences became apparent and need to be filled. In this talk, my objective is to raise awareness of the salience of communication issues in ICT projects and illustrate, what can be done (or what computer scientists, in particular, can do) scientifically and practically, to fill the research/practice gaps and concurrently improve communication, leadership, and teamwork in ICT projects.
- 27. 2. 2018
- asst. prof. Dimitris Sacharidis, Ph.D., Institute of Information Systems Engineering, TU Wien
- Managing and Analyzing Big Geo-Social Data
- Abstract: The widespread adoption of online social networks and location-aware mobile devices has resulted in a continuously increasing amount of published user-generated, geo-tagged content. Typical examples include tweets, check-ins, photo/video uploads, route posts (e.g., taxi rides, running trails). This big geo-social data essentially captures people's everyday interactions between the physical and digital world, and presents immense opportunities for creating added value to domains such as location-based services, smart cities, tourism. In this talk, we will present methods for efficiently handling and effectively analyzing large amounts of such data.
- 6. 3. 2018
- RNDr. Robert Ganian, Ph.D., Algorithms and Complexity Group, TU Wien
- Backdoors to Tractability for Constraint Satisfaction
Constraint Satisfaction (CSP) is one of the most studied NP-complete
problems, with numerous applications in both theory and practice and
featuring its own dedicated conference. A significant amount of
research has targeted the identification of classes of CSP instances
which are polynomially tractable; this has led to celebrated results
such as Schaefer's Dichotomy Theorem and Bulatov's recent proof of the
Feder-Vardi Dichotomy Conjecture. Such classes of instances are often
called "islands of tractability".
In this talk, we will present techniques and recent developments on solving CSP instances that lie outside of an island of tractability. In particular, we will use the notion of "backdoors" to capture the distance of an instance from an island of tractability and show how these backdoors can be exploited to obtain algorithms for CSP with good runtime guarantees.
- 13. 3. 2018
- Atreyee Sinha, Ph.D., Computing & Information Sciences Department, Edgewood College, Madison, USA
- How Do Computers See?
Image classification is one of the most important Computer Vision problems being
addressed by researchers around the world today. Classification is the task of labelling
images with different predefined category labels. These category labels may be based on
some low-level features such as color, texture or shape, but more often, they are based
on high-level features such as semantic description, activity or objects present.
In this talk, I will present the different techniques and recent advances in image classification and retrieval with particular examples from different applications.
- 27. 3. 2018
- Ing. Vlad Popovici, M.Sc., Ph.D., PřF MU
- Case studies in multimodal biomarker discovery
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.
• V. Popovici et al. Joint analysis of histopathology imaging features and gene expression in breast cancer. BMC Bioinformatics. 2016, 17(209).
• V. Popovici et al. Identification of "BRAF-Positive" Cases Based on Whole-Slide Image Analysis. Biomed Research International. 2017, issue: April 24
• V. Popovici et al. Image-based biomarkers for molecular subtypes of colorectal cancer. Bioinformatics. 2017, 33(13): 2002-2009
- 3. 4. 2018
- doc. JUDr. Radim Polčák, Ph.D., PrF MU
- Liability of Autonomous Robots
- Abstract: In my note, I would like to discuss some legal issues related to development and use of autonomous robots. One of obvious problems is liability. Robots do not have legal personalities, so it is questionable who and for what should be liable when a robot causes harm (physical or other - e.g. through discriminatory decisions). In real life, this issue translates mostly to compliance and modelling insurance schemes that technically define basic parameters of respective markets. In addition, I would like to briefly discuss legal barriers to use of different types of data for development or operations of robots. In that regards, we need complex legal solutions (not necessarily legislation - e.g. contractual data trusts) to overcome complicated and differentiated legal obstacles that prevent pooling and use of data from different jurisdictions within the EU and offshore.