Informatics, TU Vienna

Courses, Talks, Events


Courses 2018/2019


Fundamental Courses - Summer Semester

195.079 Fundamental Research Methods for Doctoral Students
Start of the course: March 5, 2019

Area Courses - Summer Semester

199.083 Talent Engineering - From Purpose to Impact
Prof. Martin Gaedke, TUC Chemnitz University of Technology / Germany
Course schedule: March 18-22, 2019, second bock tbc.

199.084 Memory Systems and Memory-Centric Computing Systems: Fundamentals and Recent Research Prof. Onur Mutlu, ETH Zurich
Course schedule: June 2019

199.085 Recommender Systems Team Project
Prof. Derek Bridge, University College Cork / Ireland
Course schedule: May - June 2019


Elective courses - Summer Semester

Effective Research Project Proposal Writing for Public Funding: Write up Your Research Ideas:
Further information can be found here

195.072 Current Trends in Computer Science (Ring lecture with talks given by the visiting professors of the current study year 2018/19)

Further information about the courses of the summer semester will be announced as soon as possible.



Fundamental Courses - Winter Semester

195.080 Philosophy of Science (Prof. Christiane Floyd)

195.098 Research and Career Planning for Doctoral Students


Area Courses - Winter Semester

199.081 Design, Creativity, Learning, and Human-Centered Computing — Exploring Foundations and Themes for the Future of the Digital Age
Prof. Gerhard Fischer, University of Colorado

199.082 Machine Learning Security
Prof. Siddharth Garg, New York University / Tandon School of Engineering
Course schedule: Jan 2019.


Elective courses - Winter Semester

195.072 Current Trends in Computer Science (Ring lecture with talks given by the visiting professors of the current study year 2018/19)

Further information about the courses of the winter semester will be announced as soon as possible.


Courses 2017/2018


Fundamental Courses - Summer Semester

195.079 Fundamental Research Methods for Doctoral Students

195.098 Research and Career Planning or Doctoral Students


Area Courses - Summer Semester

199.079 DataFlow SuperComputing for BigData Analytics (Prof. Veljko Milutinovic)

195.104 Engineering Self-Adaptive Systems (Prof. Danny Weyns, Katholieke Universiteit Leuven)

199.080 Real Virtuality: Authentic virtual experiences (Prof. Alan Chalmers, University of Warwick)


Elective courses - Summer Semester

Effective Research Project Proposal Writing for Public Funding: Write up Your Research Ideas:
Further information can be found here

195.072 Current Trends in Computer Science (Ring lecture with talks given by the visiting professors of the current study year 2017/18)

Computer Science track core course (K. Chatterjee, K. Pietrzak, V. Kolmogorov)
Details here:

Further information about the courses of the summer semester will be announced as soon as possible.


Fundamental Courses - Winter Semester

195.098 Research and Career Planning for Doctoral Students


Area Courses - Winter Semester

195.099 Concurrency Theory (Prof. Carlos Olarte, Universidade Federal do Rio Grande do Norte)

195.100 Healthcare in domestic settings, a CSCW perspective (Prof. Myriam Lewkowicz, Troyes University of Technology)

195.101 Quantitative evaluation of concurrent systems with stochastic temporal parameters (Prof. Enrico Vicario / University of Florence)


Elective courses - Winter Semester

195.072 Current Trends in Computer Science (Ring lecture with talks given by the visiting professors of the current study year 2017/18)

184.782 Meilensteine im Lösen von Spielen über Graphen (Sasha Rubin)



Courses 2016/2017

Fundamental Courses - Summer Semester

195.079 Fundamental Research Methods for Doctoral Students


Visiting Professor Courses - Summer Semester

195.080 Philosophy of Science (Fundamental course, Prof. Christiane Floyd)

195.092 Algorithm Design in Different Models of Computation (Prof. Guy Even, Tel-Aviv University)

195.091 Advances and Challenges in Vision Science (Prof. Oge Marques, Florida Atlantic University)

195.093 Metamodeling (Prof. Thomas Kühne, Victoria University of Wellington)

195.072 Current Trends in Computer Science (Ring lecture with talks given by the visiting professors of the current summer term)

195.094 From Web Data to Network Analyis (Prof. Alessandro Provetti, Birkbeck / University of London)


Fundamental Courses - Winter Semester

195.013 Research and Career Planning for Doctoral Students

Courses 2015/2016

Fundamental Courses - Winter Semester

195.013 Research and Career Planning for Doctoral Students


Visiting Professor Courses - Winter Semester

195.084 Graph Partitioning and Graph Clustering in Theory and Practice (Dr. Christian Schulz, Karlsruhe Institute of Technology, Germany)

195.085 Domain and Requirements: Science & Engineering (Prof. Dines Bjørner, Technical University of Denmark)

Courses 2014/2015

Fundamental Courses - Summer Semester

195.079 Fundamental Research Methods for Doctoral Students

195.080 Philosophy of Science


Visiting Professor Courses - Summer Semester

195.078 Model Predictive Control (Dr. Davide Raimondo, University of Pavia, Italy)

195.083 Social Network Analysis (Prof. Noshir Contractor, Northwestern University, USA)

195.082 Automata-theoretic methods for infinite-state verification (Prof. Tomáš Vojnar, Brno University of Technology, Czech Republic)


Fundamental Courses - Winter Semester

195.013 Research and Career Planning for Doctoral Students


“The Journey of Research in Computing: Basic versus Applied Research – Specialization versus Multidisciplinarity”, Dec 12, 2018

Key-note talk by Kaushik Roy, Purdue University, followed by a panel dicussion. More information about this upcoming event available here


Invited talks within the lecture series on current trends in computer science


The lecture series Current Trends in Computer Science will be offered for all computer science students. In this lecture series, the visiting professors of the PhD School will give a presentation about their research area.


Processing Data Where It Makes Sense in Modern Computing Systems: Enabling In-Memory Computation

Speaker: Onur Mutlu, ETH Zurich

Date: 18.06.2019, 15:00 c.t.

Location: EI9 Hlawka HS, Gusshausstrasse 27-29, ground floor

Today's systems are overwhelmingly designed to move data to computation. This design choice goes directly against at least three key trends in systems that cause performance, scalability and energy bottlenecks: 1) data access from memory is already a key bottleneck as applications become more data-intensive and memory bandwidth and energy do not scale well, 2) energy consumption is a key constraint in especially mobile and server systems, 3) data movement is very expensive in terms of bandwidth, energy and latency, much more so than computation. These trends are especially severely-felt in the data-intensive server and energy-constrained mobile systems of today.

At the same time, conventional memory technology is facing many scaling challenges in terms of reliability, energy, and performance. As a result, memory system architects are open to organizing memory in different ways and making it more intelligent, at the expense of slightly higher cost. The emergence of 3D-stacked
memory plus logic, the adoption of error correcting codes inside the latest DRAM chips, and intelligent memory controllers to solve the RowHammer problem are an evidence of this trend.

In this talk, I will discuss some recent research that aims to practically enable computation close to data. After motivating trends in applications as well as technology, we will discuss at least two promising directions: 1) performing massively-parallel bulk operations in memory by exploiting the analog operational properties of DRAM, with low-cost changes, 2) exploiting the logic layer in 3D-stacked memory technology in various ways to accelerate important data-intensive applications. In both approaches, we will discuss
relevant cross-layer research, design, and adoption challenges in devices, architecture, systems, applications, and programming models. Our focus will be the development of in-memory processing
designs that can be adopted in real computing platforms and real data-intensive applications, spanning machine learning, graph processing, data analytics, and genome analysis, at low cost. If time
permits, we will also discuss and describe simulation and evaluation infrastructures that can enable exciting and forward-looking research in future memory systems, including Ramulator and SoftMC.

Onur Mutlu is a Professor of Computer Science at ETH Zurich. He is also a faculty member at Carnegie Mellon University, where he previously held the Strecker Early Career Professorship. His current
broader research interests are in computer architecture, systems, hardware security, and bioinformatics. A variety of techniques he, along with his group and collaborators, has invented over the years
have influenced industry and have been employed in commercial microprocessors and memory/storage systems. He obtained his PhD and MS in ECE from the University of Texas at Austin and BS degrees in
Computer Engineering and Psychology from the University of Michigan, Ann Arbor. He started the Computer Architecture Group at Microsoft Research (2006-2009), and held various product and research positions
at Intel Corporation, Advanced Micro Devices, VMware, and Google. He received the inaugural IEEE Computer Society Young Computer Architect Award, the inaugural Intel Early Career Faculty Award, US National Science Foundation CAREER Award, Carnegie Mellon University Ladd Research Award, faculty partnership awards from various companies, and a healthy number of best paper or "Top Pick" paper recognitions at various computer systems, architecture, and hardware security venues. He is an ACM Fellow "for contributions to computer architecture research, especially in memory systems", IEEE Fellow for
"contributions to computer architecture research and practice", and an elected member of the Academy of Europe (Academia Europaea).


Context-Driven Recommendations based on User Reviews

Speaker: Derek Bridge, University College Cork, Ireland

Date: 29.05.2019, 14:00 c.t.

Location: EI2 Pichelmayer HS, Gusshausstrasse 25, second floor

Recommender systems are ubiquitous: from Netflix to Spotify and beyond. But recommendations should not only be personalized; often they need to be contextualized too. However, many context-aware and context-driven recommender systems use a very limited representation of context. We show how we use topic modeling to mine user reviews to obtain a much richer, open-ended context representation that we can incorporate into a context-driven recommender system.

Derek Bridge is a professor of Computer Science in the School of Computer Science and Information Technology at University College Cork, Ireland. He has over 30 years' experience of teaching and research in Artificial Intelligence. He has a PhD in computational linguistics from the University of Cambridge. But he is best known for his research in Case-Based Reasoning and Recommender Systems. In Ireland, he is one of the Principal Investigators in the Insight Centre for Data Analytics, where at national level he leads the Recommender Systems Group, and he is also a Co-Leader of the Centre for Research Training in AI.


Secure, Low Power and Reliable Implementations of Deep Learning

Speaker: Siddharth Garg, New York University

Date: 14.01.2019, 15:00 c.t.

Location: EI4 Reithoffer HS, Gusshausstrasse 25, second floor

This talk will provide an overview of the research activities in my group on secure, reliable and energy-efficient implementations of deep neural networks. The first part of the talk will highlight emerging security vulnerabilities in deep learning, specifically, on how deep learning models can be "backdoored" via training data poisoning. Backdoored Neural Networks (or BadNets) behave normally on validation data but misbehave on certain backdoored inputs, for example, stop signs with PostIt notes stuck on them. The second part of the talk will highlight our work on robust and energy-efficient hardware implementations for deep neural network based inference. We will show how the power consumption of Google TPU like architectures can be cut in half without impacting performance or accuracy.

Siddharth Garg received his Ph.D. degree in Electrical and Computer Engineering from Carnegie Mellon University in 2009, and a B.Tech. degree in Electrical Enginerring from the Indian Institute of Technology Madras. He joined NYU in Fall 2014 as an Assistant Professor, and prior to that, was an Assistant Professor at the University of Waterloo from 2010-2014. His general research interests are in computer engineering, and more particularly in secure, reliable and energy-efficient computing.

In 2016, Siddharth was listed in Popular Science Magazine's annual list of "Brilliant 10" researchers. Siddharth has received the NSF CAREER Award (2015), and paper awards at the IEEE Symposium on Security and Privacy (S&P) 2016, USENIX Security Symposium 2013, at the Semiconductor Research Consortium TECHCON in 2010, and the International Symposium on Quality in Electronic Design (ISQED) in 2009. Siddharth also received the Angel G. Jordan Award from ECE department of Carnegie Mellon University for outstanding thesis contributions and service to the community. He serves on the technical program committee of several top conferences in the area of computer engineering and computer hardware, and has served as a reviewer for several IEEE and ACM journals.


Exploring Design Trade-Offs for Quality of Life in Human-Centered Design

Speaker: Gerhard Fischer, University of Colorado Boulder, USA

Date: 22.10.2018, 17:00

Location: Kontaktraum, Gusshausstrasse 27-29, 6th floor

Creating a transformative framework to foster, nurture, and support “Quality of Life (QoL)” is one of the most challenging design problems of the digital age. QoL is a broad concept without a precise, generally accepted definition. In design, trade-offs are universal because there are no best solutions independent of goals, objectives, and values, specifically for systemic, ill-defined, and wicked problems such as QoL.
Grounded in research activities from a broad spectrum of different disciplines and an analysis from our research over the last two decades, this presentation will explore specific design trade-offs. The insights and arguments are summarized in requirements for the design of socio-technical environments to address future challenges for human-centered design grounded in a QoL perspective.

Gerhard Fischer is a Professor Adjunct and Professor Emeritus of Computer Science, a Fellow of the Institute of Cognitive Science, and the Director of the Center for Lifelong Learning and Design (L3D) at the University of Colorado at Boulder. He is a member of the Computer Human Interaction Academy, a Fellow of the Association for Computing Machinery, and a recipient of the RIGO Award of ACM-SIGDOC. In 2015, he was awarded an honorary doctorate from the University of Gothenburg, Sweden.

His research has focused on new conceptual frameworks and new media for learning, working, and collaborating, human-centered computing, and design. His recent work is centered on quality of life in the digital age, social creativity, meta-design, cultures of participation, design trade-offs, and rich landscapes for learning.


Toward Whole Cell Mesoscale Models

Speaker: Arthur Olson, The Scripps Research Institute, USA

Date: 05.10.2018, 10:30

Attention: the room has been changed!
New location: EI5 Hochenegg HS, Gusshausstrasse 25-29, (room-no. CF0229)

The ability to create structural models of cells and cellular components at the molecular level is being driven by advances ranging from proteomics and expression profiling to ever more powerful imaging approaches. It is being enabled by technology leaps in computation, informatics, and visualization. 
Our CellPACK program is a tool for generating structural models of cellular environments at molecular and atomic level.  Recently we have implemented a GPU-based implementation of CellPACK that speeds up the process by orders of magnitude, in what we have termed “instant packing.” This enables interactive exploration and manipulation of components of the packings.  Visualization of these models is also enabled by GPU-based efficient representations, renderings and levels of detail.  The ability to model complex cellular components such as a bacterial nucleoid and distinct phases is a significant challenge that we continue to work on.  Our Lab’s recent lattice-based method for rapidly producing bacterial nucleoids is a prototype for other rule-based generative structure builders.  Use of GPU-based physics engines enables real time interaction with dynamic models.  Flexx is a real-time constraint solver from NVidia.  It is capable of interactive constraint minimization of up to 1 million particles in real time.  Such systems can quickly resolve clashes and identify interactions in the crowded cellular environment.
In a parallel effort to CellPACK, we have developed CellPAINT, which has its origins in David Goodsell’s watercolor paintings of cellular environments and processes. Cellpaint uses a painting metaphore to enable creation of Goodsell-like images interactively within a Unity game-engine.  These images can be animated using a simple Brownian motion-based diffusion model.  Recently we have expanded this interactive interface into 3D, and have also implemented it in a Virtual Reality environment.

The talk will include live interactive demonstrations of the current state of our software.

Arthur Olson is the Anderson Research Chair Professor in the Department of Integrative Structural and Computational Biology at The Scripps Research Institute and founder and director of its Molecular Graphics Laboratory.  He received his Ph.D. from the University of California, Berkeley in Physical Chemistry developing computational methods in X-ray crystallography.  As a Damon Runyon postdoctoral fellow at Harvard he published on the first atomic resolution structure of an intact viral capsid. Before moving to Scripps, he served as Assistant Director of the National Resource for Computation in Chemistry at Lawrence Berkeley National Laboratory.

For over 35 years Olson has pioneered the analysis and visualization of biological assemblies spanning length scales from angstroms to microns. His laboratory has developed AutoDock and AutoDock Vina, which are the world’s most highly cited ligand protein docking programs. Olson served as Director of the NIH funded HIV Interactions and Viral Evolution (HIVE) Center.  In 2000 he started the first Internet distributed biomedical computing project, FightAIDS@Home, now running on over two million computers worldwide, and for which he was honored by resolution in the California State Legislature. His work in molecular visualization has focused on the development of novel and intuitive human interfaces for research and education in structural molecular biology including 3D printing and augmented reality technologies.  Over the last several years he and his colleagues have developed CellPACK/CellView to model, visualize and interact with intact cellular environments at the molecular level.  Olson’s visualizations and animations have reached a broad audience through public venues such as the Disney EPCOT center, Public television, and a number of art and science museum exhibits around the world.



Engineering Self-Managing Internet of Things

Speaker: Danny Weyns, Katholieke Universiteit Leuven, Belgium

Date: 12.04.2018, 15:00 c.t.

Location: EI 4 Reithoffer HS, Gusshausstrasse 25-29

Internet of Things (IoT) consists of tiny, battery-powered computing devices that are connected through a wireless network. Such networks are relatively cheap and easy to deploy and are therefore increasingly used for various monitoring and control applications. Important goals in IoT are energy efficiency and high packet delivery that need to be guaranteed regardless of uncertainties in the system, such as sudden changes in traffic load and network interference that is difficult to predict. Dealing with these uncertainties manually results in continuous maintenance, which is labor-intensive and inefficient. In this talk, I will introduce the basic engineering principles of self-adaptation and show how the approach enables IoT applications to manage themselves, reducing the burden on system operators.

Danny Weyns is professor at the Katholieke Universiteit Leuven. His main research interest is in software engineering of self-adaptive systems. Self-adaptation endows a system with the capability to adapt itself to deal with uncertain operating conditions. His research focuses on formalisms and design models to realize and assure self-adaptation for different quality goals, applying both architecture-based and control-based approaches. Dr. Weyns is also affiliated with Linnaeus University.



High-Fidelity Multisensory Virtual Experiences

Speaker: Alan Chalmers, University of Warwick, UK

Date: 10.04.2018, 16:00 c.t.

Location: EI 10 Fritz Paschke HS, Gusshausstrasse 27-29

Virtual environments (VEs) offer the possibility of simulating potentially complex, dangerous or threatening real world experiences in a safe, repeatable and controlled manner. They can provide a powerful and fully customizable tool for a personalised experience and allow attributes of human behaviour in such environments to be examined. However, to accurately simulate reality, VEs need to be based on physical simulations and stimulate multiple senses (visuals, audio, smell, touch, taste, temperature etc.) in a natural manner. Such environments are known as Real Virtuality. Natural delivery of multiple senses is especially important as a human’s perception may be significantly affected by interactions between all these senses. In particular, cross-modalities (the influence of one sense on another) can substantially alter the way in which a scene is perceived and the way the user behaves. At present there is no simulator available that can offer such a full sensory real-world experience. A key reason is that today’s computers are not yet powerful enough to simulate the full physical accuracy of a real scene for multiple senses in real-time.

This talk discusses how it may be possible to achieve high-fidelity multisensory virtual experiences now, because of our brain’s inability to process all the sensory input we receive at any given moment.

Alan Chalmers is a Professor of Visualisation at the International Digital Laboratory, WMG, University of Warwick, UK. He has an MSc with distinction from Rhodes University, 1985 and a PhD from University of Bristol, 1991. He has published over 200 papers in journals and international conferences on high-fidelity graphics, multi-sensory perception, High Dynamic Range (HDR) imaging, virtual archaeology and parallel rendering. He is Honorary President of Afrigraph and a former Vice President of ACM SIGGRAPH. Together with SpheronVR, a high-precision German camera company, he was instrumental in the development of the world's first HDR video camera, which was completed in July 2009. He is the Founder and a Director of the spin-out company goHDR Ltd., which aims to be the leader in the software which enables HDR technology.

Chalmers' research goal is "Real Virtuality", obtaining physically-based, multi-sensory, high-fidelity virtual environments at interactive rates through a combination of parallel processing and human perception techniques.



DataFlow SuperComputing for BigData Analytics

Speaker: Veljko Milutinovic

Date: 12.03.2018, 11:00 c.t.

Location: HS 13 Ernst Melan, Karlsplatz 13

This presentation analyses the essence of DataFlow SuperComputing, defines its advantages and sheds light on the related programming model. DataFlow computers, compared to ControlFlow computers, offer speedups of 20 to 200 (even 2000 for some applications), power reductions of about 20, and size reductions of also about 20. However, the programming paradigm is different, and has to be mastered. The talk explains the paradigm, using Maxeler as an example, and sheds light on the ongoing research, which, in the case of the speaker, was higlhy influenced by four different Nobel Laureates: (a) from Richard Feynman it was learned that future computing paradigms will be successful only if the ammount of communications is minimized; (b) from Ilya Prigogine it was learned that the entropy of a computing system would be minimized if spatial and temporal data get decoupled; (c) from Daniel Kahneman it was learned that the system software should offer options realted to approximate computing; and (d) from Andre Geim it was learned that the system software should be able to trade between latency and precision.

Life Member of the ACM, Fellow Member of the IEEE, Member of Academia Europaea, Member of the Serbian Academy of Engineering, Member of the Advisory Board of the Vienna Congress COMSULT, Member of the Scientific Advisory Board of Maxeler Technologies.
Prof. Veljko Milutinovic (1951) received his PhD from the University of Belgrade, spent about a decade on various faculty positions in the USA  (mostly at Purdue University), and was a co-designer of the DARPAs first GaAs RISC microprocessor. Later, for almost 3 decades, he taught and conducted research at the University of Belgrade, in EE, BA, MATH, and PHYS/CHEM. Now he serves as the Chairman of the Board for the Maxeler operation in Belgrade, Serbia. His research is mostly in datamining algorithms and dataflow computing, with the emphasis on mapping of data analytics algorithms onto fast energy efficient architectures. For 7 of his books, forewords were written by 7 different Nobel Laureates with whom he cooperated on his past industry sponsored projects. He has over 40 IEEE journal papers, over 40 papers in other SCI journals (4 in ACM journals), over 400 Thomson-Reuters citations, and about 4000 Google Scholar citations. Short courses on the subject he delivered so far in a number of universities worldwide: MIT, Harvard, Boston, NEU, Columbia, NYU, Princeton, Temple, Purdue, IU, UIUC, Michigan, EPFL, ETH, Karlsruhe, Heidelberg, Napoli, Salerno, Siena, Pisa, etc. Also at the World Bank in Washington DC, BNL, IBM TJ Watson, Yahoo NY, ABB Zurich, Oracle Zurich, etc.



Verification Techniques for a Network Algebra

Speaker: Carlos Olarte, ECT-UFRN, Brazil
(joint work with Linda Brodo)

Date: 16.01.2018, 14:00 c.t.

Location: HS 17 Friedrich Hartmann, Karlsplatz 13

The Core Network Algebra (CNA) is a model for concurrency that extends the point-to-point communication discipline of Milner’s CCS with multiparty interactions. Links are used to build chains describing how information flows among the different agents participating in a multiparty interaction. The inherent non-determinism in deciding both, the number of participants in an interaction and how they synchronize, makes it difficult to devise efficient verification techniques for this language. In this talk I will present a symbolic semantics and a symbolic bisimulation for CNA which are more amenable for automating reasoning. Unlike the operational semantics of CNA, the symbolic semantics is finitely branching and it represents, compactly, a possibly infinite number of transitions. We give necessary and sufficient conditions to efficiently check the validity of symbolic configurations. We also propose a smooth extension of the Hennessy-Milner logic to deal with CNA processes and symbolic transitions. Finally, I will present an executable rewriting logic specification of both the symbolic semantics and the modal logic, thus obtaining verification procedures to analyze CNA processes. I will profit this talk to give a gentle introduction to process calculi and CCS. Hence, no previous knowledge on these topics are required from the audience.

Carlos Olarte is CNPq Researcher (Level 2 - Computer Science) and assistant professor at ECT - UFRN (Brazil) since April 2014. Before that, he was associate professor at Pontificia Universidad Javeriana Cali (Colombia). He got his Ph.D. from LIX, École Polytechnique (France) in 2009 under the supervision of Prof. Catuscia Palamidessi and Prof. Frank Valencia. He has worked in declarative models for concurrency where processes can be seen as both, computing agents and formulas in a given logic. These works have found application in the specification and verification of systems in different application domains, e.g., biochemical systems, multimedia interactive systems and security protocols. His complete list of publication is available here: Publication list. In 2018, Carlos will be in a sabbatical leave and he will work at TU-Wien in the Computational Logic Group under supervision of Prof. Agata Ciabattoni.



Considering the Digitilization of the Society from a CSCW perspective

Speaker: Myriam Lewkowicz, Troyes University of Technology

Date: 23.01.2018, 15:30 ( Due to problems with the flight, the talk of Prof. Myriam Lewkowicz, which originally should have taken place on December 6, 2017, was postponed to January 23, 2018. )

Location: EI 9 Hlawka HS (Gusshausstraße 25-29)

We are experiencing a digitalization of the society, with its associated buzzwords: digital revolution, industry 4.0, Factories of the Future, BIM (Building Information Modelling), Internet of Things, Big Data… Working within CSCW, we know that these technologies are as situated within everyday material and social contexts as those that already exist or have been used in the past. But these contexts and our capacities to act in them are impacted by digital technologies in various ways (Robertson, Wagner, 2015). In this presentation, we will discuss how considering the digitalization of the society from a CSCW perspective poses some challenges. We will in particular discuss how the methodological and conceptual resources that CSCW has developed to understand the sociotechnical aspects and implications of digital technology design and use can be useful to address these challenges. We will also claim that Europe needs a generation of workers trained within CSCW to be able to conduct in-depth studies of digital technologies in use, and to design them taking into account ethical and political issues.

Robertson, T., & Wagner, I. (2015). CSCW and the Internet of Things. In ECSCW 2015: Proceedings of the 14th European Conference on Computer Supported Cooperative Work, 19-23 September 2015, Oslo, Norway (pp. 285-294). Springer.

Myriam Lewkowicz is Full Professor in Informatics at Troyes University of Technology (France), where she is head of Information System Management teaching branch and Tech-CICO research group (part of UMR CNRS 6281). She is graduated from Univ. Paris 9 Dauphine (Master of Research - 1997) and achieved her PhD at Univ. Paris 6 Pierre et Marie Curie in 2000 on “Designing Groupware for cooperative Knowledge Management”.
She obtained her Habilitation in 2012 at Compiegne University of Technology on "The role of models in designing systems for mediated collective practices - methodological, conceptual and instrumental contributions to an interdisciplinary research in CSCW. Her interdisciplinary research focuses on how to move from understanding ethnographically collaborative innovative practices toward the design of socio-technical solutions. The main application domain of her research for the last 12 years has been healthcare, in particular
in the areas of fostering social interactions among people in difficult situations, and supporting new coordination mechanisms within healthcare.  She is one of the founders of the ActiveAgeing LivingLab (ENoLL) in UTT. She was the french coordinator of 4 european projects in the "active and healthy ageing" domain (SEACW, FoSIBLE, PaeLife, TOPIC). Myriam Lewkowicz is chair-elect of EUSSET and has served on multiple program committees, including serving as COOP'10 papers co-chair (with Volker Wulf), ECSCW 2013 Work In Progress co-chair (with Tommasso Colombino), scientific co-chair for CHI 2013 and CHI 2014 for the sub-committee “Beyond the Individual” (with Mark Ackerman), ACM GROUP 2014 Working papers co-chair (with Stephan Lukosh and Michael Muller); ACM GROUP 2016 papers co-chair (with Michael Muller), Communities & Technologies 2017 General Chair (with Markus Rohde); ECSCW 2017 Exploratory papers co-chair (with Aleksandra Sarcevic)



10.05.2017: Two-Level Modelling Considered Harmful

Speaker: Thomas Kuehne, Victoria University Wellington

Date: 10.05.2017, 14:00 c.t.

Location: FH Hörsaal 5 (Freihaus)

Two-level object-oriented technology has been tremendously successful in both modelling (cf. UML) and programming (cf. Java). However, it has been shown that attempting to capture certain domains or systems with only two classification levels (i.e., objects and their types) results in accidental complexity that stems from an impedance mismatch between the subject at hand and the solution technology used to capture it. Examples for domains that can be more elegantly captured using multiple classification levels include biological taxonomies, process (meta-) models, software architectures, and systems with dynamic type levels. In this talk, I will present downsides of using two-level technology workarounds, discuss the novel classification dimension employed in multi-level modelling, explain the notion of "deep characterization", and provide a brief outlook on future multi-level research.

Thomas Kühne is an Associate Professor at Victoria University of Wellington, New Zealand. Prior to that he was an Assistant Professor at the Technische Universität Darmstadt, Germany, an Acting Professor at the University of Mannheim, Germany, and a Lecturer at Staffordshire University, UK. His research interests include model-driven development, metamodeling, and multi-level modelling. He received his Ph.D.  and M.Sc. in Computer Science from the Technische Universität Darmstadt, Germany in 1998 and 1992 respectively.


03.05.2017: A distributed algorithm for Vertex Cover based on the Local-Ratio technique

Speaker: Guy Even, Tel Aviv University

Date: 03.05.2017, 15:30

Location: EI 2 Pichelmayer HS

I will start with algorithms for approximating the minimum Vertex Cover of a graph. Two 2-approximate algorithms will be presented: the Greedy algorithm for the unweighted case and the Local-Ratio algorithm for the weighted case. The LOCAL model for distributed computation will be defined. The challenge of extending the Local-Ratio algorithm to a distributed LOCAL algorithm will be discussed. I will present the distributed algorithm of Bar-Yehuda et al. [PODC 2016] that computes a (2+eps)-approximation in (log Delta)/(eps log log Delta) rounds.

Guy Even received his B.Sc. degree in 1988 in Mathematics and Computer Science from the Hebrew University. Received his M.Sc. and D.Sc. in Computer Science from the Technion in 1991 and 1994, respectively. Dr. Even spent his post-doctorate in the University of the Saarland during 1995–1997 with Prof. Wolfgang Paul. Since 1997, he is a faculty member in the School of Electrical Engineering in Tel-Aviv University. Dr. Even is interested in algorithms and their applications in various fields. He has published papers on the theory of VLSI, approximation algorithms, computer arithmetic, online algorithms, frequency assignment, scheduling, packet-routing, linear-programming decoding of LDPC codes, and rateless codes. He is on the editorial board of "Theory of Computing Systems".  Together with Moti Medina, Dr. Even wrote a digital hardware textbook titled "Digital Logic Design: A Rigorous Approach" published in 2012 by Cambridge University Press.


27.04.2017: Can you trust what you see? The magic of visual perception

Speaker: Oge Marques, Florida Atlantic University

Date: 27.04.2017, 16:00 c.t.

Location: FH Hörsaal 5 (Freihaus)

Vision is our most developed sense and one upon which we rely to make many decisions, conscious or otherwise. Many of our everyday interactions, such as driving a car, greeting familiar faces on the street, or deciding which dish to order at a restaurant, are guided by our visual sense.
For the most part, this works well. But sometimes we are reminded of our visual system’s limitations and surprising behavior through optical illusions that exploit misjudgments in size, distance, depth, color and brightness, among many others.
This lecture presents and explains a diverse collection of visual perception phenomena that challenge our common knowledge of how well we detect, recognize, compare, measure, interpret, and make decisions upon the information that arrives at our brain through our eyes. It also explains the relationships between the latest developments in human vision research and emerging technologies, such as: self-driving cars, face recognition and other forms of biometrics, and virtual reality. 
After seeing a large number of examples of optical illusions and other visual phenomena, this talk will make you wonder: can you really trust what you see?  

Oge Marques, PhD is Professor of Computer Science and Engineering at the College of Engineering and Computer Science and, by courtesy, Professor of Information Technology and Operations Management at the College of Business, at Florida Atlantic University (FAU) (Boca Raton, Florida, USA). He is Tau Beta Pi Eminent Engineer, ACM Distinguished Speaker, and the author of more than 100 publications in the area of intelligent processing of visual information – which combines the fields of image processing, computer vision, image retrieval, machine learning, serious games, and human visual perception –, including the textbook “Practical Image and Video Processing Using MATLAB” (Wiley-IEEE Press). Professor Marques is Senior Member of both the IEEE (Institute of Electrical and Electronics Engineers) and the ACM (Association for Computing Machinery) and member of the honor societies of Sigma Xi, Phi Kappa Phi and Upsilon Pi Epsilon. He has more than 30 years of teaching and research experience in different countries (USA, Austria, Brazil, India, Spain, France, and the Netherlands).


30.03.2017: At the Core of Computing: Operational (Re-)Construction

Speaker: Christiane Floyd

Date: 30.03.2017, 14:00 c.t.

Location: EI5 Hochenegg, Gusshausstrasse 25-29

The notion of 'Computing' covers scientific fields like ‘informatics’, ‘computer science’, as well as the practice of developing computing systems and artifacts in both research and industry. ‘To be computed’ does not refer to calculation only, but to reframing a problem so as to make it accessible to operationalization. Computing systems and artifacts are so pervasive in society, they exhibit such an enormous diversity and transform our lives in so widely divergent fields that the question arises: what ties together the scientific disciplines underlying their construction and how do they relate to other sciences?
In this talk, we will be concerned with two questions:
1. What is the place of Computing in the landscape of the sciences?
2. How can we characterize Computing in the field of tension between the formal, the technical and the social world?
It will be argued that Computing comes with a thinking style – operational (re-)construction – which can be applied to most any area of interest and will be explored in some depth in the talk.

Christiane Floyd is Professor emerita for Software Engineering of the University of Hamburg and Honorary Professor at TU Wien. She was the first female professor for Computer Science in Germany. Floyd did her Ph.D. in Mathematics at the University of Vienna in 1966. From 1966 to 1968 she worked as a software engineer for Siemens, Munich. From 1968 to 1973 she was working and teaching at Stanford University. She was also senior consultant for Softlab, Munich (1973-1977). Floyd served as professor at TU Berlin (1978-1991) and University of Hamburg (1991- 2008). Together with her research group STEPS she developed a participative and evolutionary approach for software development, which laid the epistemological foundation for the field of software engineering. In 1987 she joined the board of FIfF (Forum InformatikerInnen für Frieden und gesellschaftliche Verantwortung) as a founding member and chair. In this position Floyd worked on the frontier for increasing the societal responsibility of Computer Science. In 2000 she acted as dean for the research area ICT within the “Internationale Frauenuniversität“. Since 2006 she has furthermore been active in the field of ICT for Development in Ethiopia. 


30.06.2016 Model checking and system design as a machine learning problem

Constructing an efficient statistical learning approach

Speaker: Guido Sanguinetti, University of Edinburgh

Date: 30.06.2016, 14:00

Location: Informatik Hörsaal

I will consider the problem of probabilistic model checking of temporal logic formulae on stochastic processes with parametric uncertainty. This is computationally challenging, as in principle one needs an expensive model checking step for each value of the model parameters. We show that the dependence of truth probabilities on parameters is differentiable, which allows us to construct an efficient statistical learning approach to solve the problem: we collect a sparse sample of parameter/ truth probability pairs, and treat them as a training set for a machine learning predictor based on Gaussian Processes. Due to the smoothness result, this approach converges to the true value in the large sample size. I will further discuss how these ideas can be generalised in a system design/ identification context.

Guido Sanguinetti is a Reader in Informatics at the University of Edinburgh, UK. His interests focus on machine learning methodologies for complex systems, in particular dynamical biological systems. He has published >60 research articles in leading international journals including Science, PNAS, Nature Communications. He is in receipt of an ERC Starting Grant and was awarded the 2012 PNAS Cozzarelli Prize in Engineering and Applied Science.




07.06.2016 Model Theory in Computer Science – Recurrent themes and some lessons learned

Speaker: Johann A.Makowsky, Technion – Israel Institute of Technology

Date: 07.06.2016, 14:00

Location: EI9

I give an updated version of my talk given at CSL-2011 (retiring EACSL-president's address) with the same title. I describe my research from hard core model theory to soft model theory and my transition to logic for computer science and then to logic applied to combinatorics in a leasurely way. I also add some lessons I learned about research, human memory, and science as a cultural system. It is planned for a wide audience.

Johann A. Makowsky is a distinguished mathematician working in mathematical logic and the logical foundations of computer science and combinatorics. He studied at the Swiss Federal Institute of Technologyfrom 1967-73 and held visiting positions at the Banach Center in Warsaw, Stanford University, Simon Fraser University (Canada), University of Florence, MIT, Lausanne University, and ETH Zurich. Prof. Makowsky is full professor at the Technion in Haifa. He also was a founding member of the European Association of Computer Science Logic in 1992, its vice-president (2002-2004) and president (2004-2009), and was a member of EACSL's executive council until 2014. His research includes contributions in model theory, database theory, and logic programming.



06.06.2016, Vote Counting as Mathematical Proof

Speaker: Dirk Pattinson, Australian National University

Date: 06.06.2016, 14:00

Location: EI3

We give an overview of the current state of electronic voting as used for legally binding elections throughout the world. Of particular interest is the question of trust: what mechanisms are in place (or should be) so that the various stakeholders are in fact convinced that the final outcome of an electronic election is in fact consistent with the procedures outlined in law? We then specialise this question to the question of electronic vote counting, and present an approach to universal verifiability that enables a wide range of members of the general public to convince themselves of the correctness of ballot counting.

After receiving MSc and PhD from Ludwig-Maximilians Universität, München, Dirk held academic positions at the University of Leicester and Imperial College London (both UK) before taking up his present position of Associate Professor at the Australian National University in Canberra, Australia.






01.06.2016 Do you want a Robot Lover? The Ethics of Caring Technologies

Speaker: Blay Whitby, University of Sussex

Date: 01.06.2016, 14:00

Location: EI9

Do You Want a Robot Lover? You might perhaps think that you do and that it is nobody else's business but yours, but the widespread use of robots in intimate and caring roles will bring about important social changes. We need to examine these changes now and consider them from an ethical standpoint. Robotic carers and artificial companions are a technology that is likely to be available in the near to mid‐term future. In Japan and South Korea robots are seen as potential carers for the elderly and as babysitters. Many researchers are looking to make their products display emotion and respond to emotional displays by users. At least one writer has predicted marriage to robots will be accepted in progressive countries by 2050. This talk will examine some of the implications of these ‐ both technical and social. Do they represent socially and ethically acceptable developments? What is likely to be technically feasible and just what should we allow?

Dr. Blay Whitby is a philosopher and ethicist concerned with the social impact of new and emerging technologies. He is a leading researcher in the field and the author of many books, chapters and papers on the subject including “On Computable Morality”, “Reflections on Artificial Intelligence: The Legal, Moral and Ethical Dimensions" and “Artificial Intelligence, A Beginner’s Guide”.





18.05.2016 On the Evaluation of Unsupervised Outlier Detection - Measures, Datasets, and an Empirical Study

Speaker: Arthur Zimek, Ludwig-Maximilians-Universität München

Date: 18.05.2016, 16:00

Location: GM2 Radinger Hörsaal

The evaluation of unsupervised outlier detection algorithms is a constant challenge in data mining research. Little is known regarding the strengths and weaknesses of different standard outlier detection models, and the impact of parameter choices for these algorithms. The scarcity of appropriate benchmark datasets with ground truth annotation is a significant impediment to the evaluation of outlier methods. Even when labeled datasets are available, their suitability for the outlier detection task is typically unknown. Furthermore, the biases of commonly-used evaluation measures are not fully understood. It is thus difficult to ascertain the extent to which newly-proposed outlier detection methods improve over established methods. In this talk, we discuss our recent research results: we performed an extensive experimental study on the performance of a representative set of standard k nearest neighborhood-based methods for unsupervised outlier detection, across a wide variety of datasets prepared for this purpose. Based on the overall performance of the outlier detection methods, we provide a characterization of the datasets themselves, and discuss their suitability as outlier detection benchmark sets. We also examine the most commonly-used measures for comparing the performance of different methods, and suggest adaptations that are more suitable for the evaluation of outlier detection results.

Dr. Arthur Zimek is a Privatdozent in the database systems and data mining group at the Ludwig-Maximilians-Universität München (LMU), Germany. 2012-2013 he was a postdoctoral fellow in the department for Computing Science at the University of Alberta, Edmonton, Canada. In 2014 he was a visiting professor at Technical University Vienna, Austria. He holds degrees in bioinformatics, philosophy, and theology, involving studies at universities in Munich, Mainz (Germany), and Innsbruck (Austria) and finished his Ph.D. thesis in informatics on "Correlation Clustering" at LMU in summer 2008. For this work, Zimek received the "SIGKDD Doctoral Dissertation Award (runner-up)" in 2009. His research interests include ensemble techniques, clustering, and outlier detection, methods as well as evaluation, and high dimensional data. Zimek published more than 60 papers at peer reviewed conferences and in international journals. Together with his co-authors, he received the "Best Paper Honorable Mention Award" at SDM 2008 and the "Best Demonstration Paper Award" at SSTD 2011. Zimek has been a member or senior member of program committees of the leading data mining conferences (e.g. SIGKDD, ECMLPKDD, CIKM, SDM) and serves as reviewer for journals like ACM TKDD, IEEE TKDE, Data Mining and Knowledge Discovery (Springer), Machine Learning (Springer).



03.05.2016 Search-Based Software Engineering, Foundations, Challenges and Recent Advances

Speaker: Marouane Kessentini, University of Michigan

Date: 03.05.2016, 15:00

Location: EI3

A growing trend has begun in recent years to move software engineering problems from human-based search to machine-based search that balances a number of constraints to achieve optimal or near-optimal solutions. As a result, human effort is moving up the abstraction chain to focus on guiding the automated search, rather than performing the search itself. This emerging software engineering paradigm is known as Search Based Software Engineering (SBSE). It uses search based optimization techniques, mainly those from the evolutionary computation literature to automate the search for optimal or near-optimal solutions to software engineering problems. The SBSE approach can and has been applied to many problems in software engineering that span the spectrum of activities from requirements to maintenance and reengineering. Several challenges have to be addressed to mainly tackle the growing complexity of software systems nowadays in terms of number of objectives, constraints and inputs/outputs. Most of software engineering problems are multi- and many-objective by nature to find a trade-off between several competing goals. In addition, several software engineering solutions lack robustness due to the dynamic environments of software systems (e.g., requirements change over time). Furthermore, it is essential to understand the points at which human oversight, intervention, resumption-of-control and decision making should impinge on automation. In this talk, I will give, first, an overview about SBSE then I will focus on some contributions that I proposed, along with my research group and my industrial partners. Finally, I will discuss possible new research directions in SBSE.

Dr. Marouane Kessentini is an Assistant Professor in the Department of Computer and Information Science at the University of Michigan. He is the founder of the Search-Based Software Engineering (SBSE) research lab. He has several collaborations with different industrial companies on the use of computational search, machine learning and evolutionary algorithms to address several software engineering problems such as software quality, software testing, software migration, software evolution, etc. He received a best PhD award from University of Montreal in 2012 and a Presidential BSc Award from the President of Tunisia in 2007. He received many grants from both industry and federal agencies and published around 70 papers in software engineering journals and conferences, including 3 best paper awards. He is also the founder of the North American Symposium on Search Based Software Engineering, funded by the National Science Foundation (NSF), and a guest editor of the first Special Issue on Search Based Software Engineering at the IEEE Transactions on Evolutionary Computation Journal (2016). He is an invited speaker in the 2016 IEEE World Congress on Computational Intelligence (Vancouver, Canada).



28.01.2015 Big Data Graph Algorithms

Speaker: Christian Schulz, Karlsruhe Instititute of Technology

Date: 28.01.2015, 13:00

Location: EI2

The talk covers recent work on big data graph algorithms. We touch three different areas: graph partitioning, graph drawing and kernelization techniques for the independent set problem in practice. In particular, we present parallel partitioning algorithms that are able to process huge complex networks which have recently attracted considerable interest. We engineer parallel size-constraint graph clustering algorithms that are used as a subroutine at multiple stages of multilevel graph partitioning. The resulting system is more scalable and achieves higher quality than other state-of-the-art systems. As an example, we partition a web graph with 3.3G edges in 16 seconds on a high-performance cluster and compute a high quality partition -- none of the competing systems can handle this graph. In another line of research, we compute graph layouts using a multilevel algorithm with respect to a recently proposed metric that combines layout stress and entropy. Drawing large graphs appropriately is an important step for the visual analysis of data from real-world networks. The proposed system uses a simple local iterative scheme within a multilevel approach, approximates long-range forces and uses shared-memory parallelism. In comparison to the previously best maxent-stress optimizer, which is sequential, our parallel implementation is on average 30 times faster while producing comparable solution quality. Lastly, we develop an advanced evolutionary algorithm, which incorporates kernelization techniques to compute large independent sets in huge sparse networks. The key idea is to apply an evolutionary algorithm on a problem kernel, and then proceed recursively with inexact kernelization techniques. This opens up the reduction space, which not only speed up the computation of large independent sets drastically, but also enabled us to compute high-quality independent sets on much larger instances than previously reported in the literature.

Christian Schulz is currently a visiting researcher at the TU Wien and a postdoctoral researcher at the Karlsruhe Institute of Technology (KIT). He obtained his master degrees in mathematics and computer science as well as his Ph.D with summa cum laude at the KIT. He was the best student of the year 2010 of the faculty of informatics of the KIT and received multiple awards for his dissertation. His graph partitioning algorithms -- KaHIP -- have been able to improve or reproduce most of the benchmark entries in the Walshaw Benchmark and scored most of the points in the 10'th DIMACS Implementation Challenge on Graph Partitioning and Clustering.



29.10.2015 A New Foundation for Computing Science

Speaker: Dines Bjørner, Technical University of Denmark

Date: 29.10.2015, 14:00

Location: HS1, Theresianumgasse 27

We argue that computing systems requirements must be based on precisely described domain models. We further argue that domain science and engineering offers a new dimension in computing. We review our work in this area and we hint at a research and experimental engineering programme for the first two phases of the triptych of domain engineering, requirements engineering, and software design.

Dines Bjørner is professor emeritus at the Technical University of Denmark in Lyngby. He was also responsible for establishing the United Nations University International Institute for Software Technology (UNU-IIST) in Macau. His research deals with domain engineering, requirements engineering, and formal methods. Moreover, he worked on the Vienna Development Method (VDM) at IBM in Vienna as well as being involved in realizing the RAISE (Rigorous Approach to Industrial Software Engineering) formal method with tool support.



10.06.2015 From Pointers to List Containers

Speaker: Tomáš Vojnar, Brno University of Technology, Czech Republic.

Attention: Talk had to be postponed!

Date: 10.6.2015, 16:00

Location: EI2

We propose a method that transforms a C program manipulating lists via low-level pointer statements into an equivalent program where the lists are manipulated via calls of standard high-level container operations like push_back, pop_front, etc. The input of our method is a C program annotated by a special form of shape invariants which can be obtained from current automatic shape analysers. The resulting program where low-level pointer statements are summarized into high-level container operations is more understandable and better suitable for program analyses since the burden of analysing low-level pointer manipulations gets removed. We have implemented our approach and successfully tested it through a number of experiments, including experiments showing that our method can indeed be used to ease program analysis by separating shape analysis from analysing data-related properties. The result is a joint work with Kamil Dudka, Lukas Holik, and Petr Peringer from Brno University of Technology and Marek Trtik from Verimag, Grenoble.

Tomas Vojnar received his PhD at the Brno University of Technology (BUT) in 2001. From 2001 to 2003, he worked as a postdoc researcher at LIAFA, Université Paris Diderot. Since 2003, he works at the Faculty of Information Technology of BUT. He defended his habilitation thesis in 2007 and became a full professor in 2012. His research focuses mainly on automated verification, especially over infinite-state and concurrent systems. In the former area, his work has included formal verification of parameterized systems, abstract regular model checking, and shape analysis of programs with pointers and dynamic linked data structures. He has also worked on efficient ways of dealing with various kinds of non-deterministic automata and logics, with applications in the above mentioned verification approaches. As for concurrent programs, he has mainly worked in the area of their noise-based testing and dynamic analysis, self-healing, as well as applications of search techniques in noise-based testing. He has (co-)authored over 100 scientific publications as well as multiple software tool prototypes (e.g., Forester, Predator, SearchBestie, AnaConDA, Spen, or Slide). These works won multiple best paper awards, such as the EATCS Best Theory Paper Award of ETAPS'10, the best tool paper of RV'12, as well as multiple medals in the international software verification competition SV-COMP'12-15, including a Goedel medal at the FLoC Olympic Games 2014.


09.06.2015 Leveraging Computational Social Science to address Grand Societal Challenges

Speaker: Noshir S. Contractor, Northwestern University, USA.

Date: 09.06.2015, 17:00

Location: EI2

The increased access to big data about social phenomena in general, and network data in particular, has been a windfall for social scientists. But these exciting opportunities must be accompanied with careful reflection on how big data can motivate new theories and methods. Using examples of his research in the area of networks, Contractor will argue that Computational Social Science serves as the foundation to unleash the intellectual insights locked in big data. More importantly, he will illustrate how these insights offer social scientists in general, and social network scholars in particular, an unprecedented opportunity to engage more actively in monitoring, anticipating and designing interventions to address grand societal challenges.

Noshir Contractor is the Jane S. & William J. White Professor of Behavioral Sciences in the McCormick School of Engineering & Applied Science, the School of Communication and the Kellogg School of Management at Northwestern University, USA. He is the Director of the Science of Networks in Communities (SONIC) Research Group at Northwestern University and a board member of the Web Science Trust. He is investigating factors that lead to the formation, maintenance, and dissolution of dynamically linked social and knowledge networks in a wide variety of contexts.
His research program has been funded continuously for almost two decades by major grants from the U.S. National Science Foundation with additional funding from the U.S. National Institutes of Health (NIH), Army Research Laboratory, Air Force Research Laboratory, Army Research Institute, NASA, Rockefeller Foundation, Gates Foundation, and the MacArthur Foundation.
His book titled Theories of Communication Networks (co-authored with Professor Peter Monge and published by Oxford University Press), received the 2003 Book of the Year award from the Organizational Communication Division of the National Communication Association. He was a recipient of the 2014 National Communication Association Distinguished Scholar Award and in 2015 he was elected a Fellow of the International Communication Association. He is also the co-founder and Chairman of Syndio, which offers organizations products and services based on network analytics.
Professor Contractor has a Bachelor’s degree in Electrical Engineering from the Indian Institute of Technology, Madras and a Ph.D. from the Annenberg School of Communication at the University of Southern California.


01.06.2015 Image processing applications in small and big scales

Speaker: László G. Nyúl, Szeged University, Hungary.

Date: 01.6.2015, 14:00

Location: EI3

The main task of digital image processing is to process and analyze image-like data. Data from any source can be understood as an image if it can be represented in a matrix form. Most often we deal with images of 2 or 3 spatial dimensions, but time (e.g. in video sequences) and spectral dimensions (e.g. in aerial remote sensing) can also be handled. Among others, image processing deals with image restoration (the compensation for degradation), image segmentation (the delineation of objects depicted in the image), image registration (determining the spatial correspondence between images acquired at different time and/or space), image fusion (forming a new image by combining the information from multiple images), calculating object properties and describing the objects and/or the scene depicted in the image. Image processing is applied in an increasing number of areas in life, such as in medical image diagnosis systems, industrial manufacturing and quality control, security systems, from autonomous robots to smartphones with cameras. In this lecture the audience shall get a taste of these topics and challenges through selected projects from the half century history of image processing at the University of Szeged.

László G. Nyúl has received his degrees in mathematics and computer science from the University of Szeged, Hungary. Currently he is the Head of the Department of Image Processing and Computer Graphics, Faculty of Science and Informatics, University of Szeged. Between 2011 and 2014 he has been deputy head of the Institute of Informatics at the University of Szeged. His research interest is digital image processing with a focus on medical applications and fuzzy approaches. Since 1991 he lectures at the University of Szeged in various subjects, including Computer graphics, Graphical systems, Advanced graphics algorithms, Multimedia, Image processing, Fuzzy techniques in image processing, Image databases, and Medical imaging.


12.05.15 Search for the Science of Computing: Competing Viewpoints

Speaker: Matti Tedre, University of Stockholm, Sweden.

Date: 12.5.2015, 16:00

Location: HS 8

Computing as a discipline started form up after a new era of computing dawned in the 1930s and 1940s with a number of technical and theoretical innovations. Clashes between different agenda for the nascent field characterized computing's disciplinary debates from the beginning. One of the early dilemmas was to describe computing as a rigorous, mathematically oriented field separate from mathematics. The software crisis brought up arguments for the importance of software engineering as well as studying people, the users of computer systems. All along computing was also characterized as an empirical science - first by virtue of its theoretical foundations, and then by virtue of its aims, methods, subject matter, and computational modeling's predictive success in other fields. This talk discusses some central debates about computing's disciplinary identity and their importance for the discipline's formation.

Matti Tedre is the author of The Science of Computing: Shaping a Discipline (Taylor & Francis / CRC Press, 2014). He's an associate professor at Stockholm University, and an adjunct professor in several other universities. His main fields of interest are the history and philosophy of computer science and computer science education research.


13.04.15 Real-time Model Predictive Control for the Optimal Charging of a Lithium-ion Battery

Speaker: Davide M. Raimondo, University of Pavia, Italy.

Date: 13.4.2015, 14:00

Location: EI 9

Li-ion batteries are widely used in industrial applications due to their high energy density, slow material degradation, and low self-discharge. The existing advanced battery management systems (ABMs) in industry employ semi-empirical battery models that do not use first-principles understanding to relate battery operation to the relevant physical constraints, which results in conservative battery charging protocols. In this talk we present a Quadratic Dynamic Matrix Control (QDMC) approach to minimize the charge time of batteries to reach a desired state of charge (SOC) while taking temperature and voltage constraints into account. This algorithm is based on an input-output model constructed from a first-principles electrochemical battery model known in the literature as the pseudo two-dimensional (P2D) model. In simulations, this approach is shown to significantly reduce charging time.

Davide M. Raimondo was born in Pavia, Italy, in 1981. He received the B.Sc. and M.Sc. in Computer Engineering, and the Ph.D. in Electronic, Computer Science and Electric Engineering from the University of Pavia, Italy, in 2003, 2005, and 2009, respectively. As a Ph.D. student he held a visiting position at the Department of Automation and Systems Engineering, University of Seville, Spain. From January 2009 to December 2010 he was a postdoctoral fellow in the Automatic Control Laboratory, ETH Zürich, Switzerland. From March 2012 to June 2012 and from August 2013 to September 2013 he was visiting scholar in Prof. Braatz Group, Department of Chemical Engineering, MIT, USA. Since December 2010 he is Assistant Professor at University of Pavia, Italy. He is the author or coauthor of more than 50 papers published in refereed journals, edited books, and refereed conference proceedings. His current research interests include control of nonlinear constrained systems, robust control, networked control, fault-tolerant control, autonomous surveillance and control of glycaemia in diabetic patients. Dr. Raimondo co-organized the NMPC Workshop on Assessment and Future Direction, Pavia, Italy, in 2008. He was also co-organizer of the invited sessions Nonlinear Model Predictive Control, for IFAC NOLCOS 2010, and New Developments in Nonlinear Model Predictive Control, for IFAC NOLCOS 2007. He served as an Associate Editor of IFAC NOLCOS 2010 and as member of the Nonlinear Model Predictive Control 2012 (NMPC'12) and European Control Conference 2013 (ECC'13) International Program Committees.


22.05.14 Building Applications for the Cloud: The Wrong, the Right, the Solid Way

Speaker: Frank Leymann, University of Stuttgart, Germany.

Date: 22.5.2014, 15:30

Location: EI10

Since the advent of Cloud Computing Technology the question of how to use the cloud for moving existing applications to the cloud or how to build new applications for the cloud gets more and more pressing. In our talk we describe the major pitfall to avoid, namely simply bursting virtual images of stacks of applications to the cloud. Next, we describe the TOSCA standard that is targeted towards applications that are portable across multiple cloud environments, and that fosters application structures that make use of cloud benefits. Finally, we motivate the uses of best practices (“patterns”) of how to architect applications that fit best into a cloud environment.

Frank Leymann is a full professor of computer science and director of the Institute of Architecture of Application Systems (IAAS) at the University of Stuttgart, Germany. His research interests include service-oriented architectures and associated middleware, workflow- and business process management, cloud computing and associated systems management aspects, and patterns. Before accepting the professor position at University of Stuttgart he worked for two decades as an IBM Distinguished Engineer where he was member of a small team that was in charge of the architecture of IBM’s complete middleware stack.


19.05.14 Active Fault Diagnosis for Uncertain Systems

Speaker: Davide Raimondo, University of Pavia, Italy.

Date: 19.05.2014, 16:30

Place: EI2

Component malfunctions and other faults pose a significant threat to the safety and efficiency of complex systems, such as aircrafts, power systems, and chemical plants. For these reasons, many methods have been developed to determine whether or not a fault has occured (fault detection) and, if so, the nature of the fault (fault diagnosis). The vast majority of these methods are passive, meaning that the fault status is decided on the basis of input-output data acquired during normal control operation. However, faults are not always detectable at normal operating conditions, or are obscured by the action of the control system itself. Active fault diagnosis involves injecting a suitably designed input into the system to improve the detectability and diagnosability of potential faults. The use of such inputs has clear potential for overcoming a central difficulty in fault detection, which is to distinguish the effects of faults from those of disturbances, process uncertainties, etc. This presentation discusses new methods for computing active inputs that guarantee that the input-output data of a process will be sufficient to correctly identify a fault from a given library of possible faults. To address this problem, a new formulation is considered, along with related approximations, that is amenable to efficient solution using standard optimization packages (e.g. CPLEX). The theoretical contributions combine ideas from reachability analysis, set-based computations, and optimization theory to exploit detailed problem structure and thereby manage the problem complexity.

Davide M. Raimondo was born in Pavia, Italy, in 1981. He received the B.Sc. and M.Sc. in Computer Engineering, and the Ph.D. in Electronic, Computer Science and Electric Engineering from the University of Pavia, Italy, in 2003, 2005, and 2009, respectively. As a Ph.D. student he held a visiting position at the Department of Automation and Systems Engineering, University of Seville, Spain. From January 2009 to December 2010 he was a postdoctoral fellow in the Automatic Control Laboratory, ETH Zürich, Switzerland. From March 2012 to June 2012 and from August 2013 to September 2013 he was visiting scholar in Prof. Braatz Group, Department of Chemical Engineering, MIT, USA. Since December 2010 he is Assistant Professor at University of Pavia, Italy.
He is the author or co-author of more than 50 papers published in refereed journals, edited books, and refereed conference proceedings. His current research interests include control of nonlinear constrained systems, robust control, networked control, fault-tolerant control, autonomous surveillance and control of glycaemia in diabetic patients.
Dr. Raimondo co-organized the NMPC Workshop on Assessment and Future Direction, Pavia, Italy, in 2008. He was also co-organizer of the invited sessions Nonlinear Model Predictive Control, for IFAC NOLCOS 2010, and New Developments in Nonlinear Model Predictive Control, for IFAC NOLCOS 2007. He served as an Associate Editor of IFAC NOLCOS 2010 and as member of the Nonlinear Model Predictive Control 2012 (NMPC'12) and European Control Conference 2013 (ECC'13) and 2014 (ECC'14) International Program Committees.


15.05.14 There and Back Again. Outlier Detection between Statistical Reasoning and Efficient Database Methods

Speaker: Arthur Zimek, LMU München, Germany.

Date: 15.5.2014, 17:00

Place: HS 6 (Karlsplatz)

While classical statistical methods for outlier detection had a focus on probabilistic reasoning, research on outlier detection in the database context during the last decade focused on the development of ever more efficient methods to compute outlier scores without much reasoning about the meaning of these scores. In this talk, we sketch this development and introduce some methods that go back again to statistical reasoning on top of the efficient database techniques. As we demonstrate, this opens up new possibilities for the design of ensemble methods for outlier detection.

Dr. Arthur Zimek is a Privatdozent in the database systems and data mining group of Hans-Peter Kriegel at the Ludwig-Maximilians-Universität München, Germany. 2012--2013 he was a postdoctoral fellow in the department for Computing Science at the University of Alberta, Edmonton, Canada. He finished his Ph.D. thesis in informatics on "Correlation Clustering'' in summer 2008, and received for this work the ``SIGKDD Doctoral Dissertation Award (runner-up)'' in 2009. Together with his co-authors, he received the ``Best Paper Honorable Mention Award'' at SDM 2008 and the ``Best Demonstration Paper Award'' at SSTD 2011. Zimek has served in program committees (e.g. SIGKDD, ECMLPKDD, CIKM) and as reviewer for journals like ACM TKDD, IEEE TKDE, Data Min.~Knowl.~Disc., Machine Learning etc.


06.05.14 Modeling and Solving The Patient Admission Scheduling Problem

Speaker: Andrea Schaerf, University of Udine, Italy.

Date: 6.5.2014, 17:30

Place: EI2

The Patient Admission Scheduling problem consists in scheduling patients within a planning horizon into hospital rooms in such a way to maximize medical treatment effectiveness, management efficiency, and patient's comfort.
In this talk, we discuss, revisit, and extend the Patient Admission Scheduling problem proposed in the literature, in order to make it suitable for practical applications.  We propose a solution approach based on local search, which explores the search space using a composite neighborhood. In addition, we discuss an instance generator that uses real-world data and statistical distributions so as to synthesize realistic and challenging case studies. Finally, we discuss the experimental activity including statistically-principled parameter tuning methods, for both the static and the dynamic version of the problem.

Andrea Schaerf received his master degree cum laude in Electrical Engineering in 1990 and his PhD in Computer Science in 1994 from University of Rome "La Sapienza". During his studies, he spent one year at Stanford University (California, U.S.A.) under the supervision of Y. Shoham. After graduating, he was supported for one year by a scholarship from CNR, and successively he spent one year at CWI in Amsterdam under the supervision of K. Apt, supported by a fellowship by ERCIM. From 1996 to 1998 he has been Assistant Professor at University of Rome "La Sapienza". From 1998 to 2005 he has been Associate Professor at University of Udine, where, starting November 2005, he is Full Professor. His main research interest is in algorithms, specification languages, and software tools for scheduling and timetabling problems.


30.04.14 User Mobility Patterns: A Gold Mine for Intrusion Detection of Mobile Devices 

Speaker: Peter Scheuermann, Northwestern University, Evanston, Illinois, USA.

Date: 30.4.2014, 14:30

Place: EI2

Theft of confidential data by unauthorized users accounts for much of the financial losses due to computer crime. However, most user authentication techniques for portable computers require explicit authentication.  In the first part of this talk, we present an implicit re-authentication schemes for portable devices that monitors   the user specific patterns based on file system and network activities. The various parameters relevant to these activities are mapped into a multidimensional vector space and a k-means clustering algorithm is used to construct a normal user model. Intruders are detected by measuring the distance between two distribution vectors.
While the above activities are useful for some types of devices, smart phones enable us to track the user behavior by observing  spatio-temporal patterns.  In the second part of our talk we present two statistical profiling techniques that allow us to detect anomalies corresponding to intruder patterns.  Our techniques fall in the category of non-parametric collective detection anomaly models.  Probabilities are extracted from the traces and anomalies correspond to a low probability region of the stochastic model.  The first technique takes into account the location-in –time of users and computes the cumulative probabilities of trace samples. The second, considers also the transition probabilities between locations to construct the Markov sequence probabilities of trace samples.  We present the results of our experimental evaluation based on the Reality Mining and  Geolife data sets that show that our system is capable of detecting a potential intruder with 90-95% accuracy.

Peter Scheuermann is a Professor of Electrical Engineering and Computer Science at Northwestern University. He has held visiting professor positions with the Free University of Amsterdam, the Technical University of Berlin, the Swiss Federal Institute of Technology, Zurich and University of Melbourne. Dr. Scheuermann has served on the editorial board of the Communications of ACM, The VLDB Journal, IEEE Transactions on Knowledge and Data Engineering and is currently an associate editor of Data and Knowledge Enginee­ring, Wireless Networks and ACM Transactions on Spatial Algorithms and Systems (TSAS). Among his professional activities, he has served as General chair of the ACM-SIGMOD Conference in 1988,  General chair of the  ER ‘2003 Conference and  more recently as Program Co-Chair of the ACM-SIGPATIAL conference in  2009.  His research interests are in spatio-temporal databases, mobile computing, sensor networks, data warehousing and  data mining. He has published more than 140 journal and conference papers. His research has been funded by NSF, NASA, HP, Northrop Grumman, and BEA, among others. Peter Scheuermann is a Fellow of IEEE and AAAS,