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7.6.2018 11:00 - 28.9.2018 11:00 - Welcome Weekend for new admitted students

1.7.2018 - 31.8.2018 - Summer Holidays

17.9.2018 - 14.12.2018 - Classes in Fall Semester 2018/2019

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2017 – Guest Lecturers

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Stephan Proksch – Conflict Management and Mediation

Johannes Fürnkranz – Inductive Rule Learning – CANCELLED (due to illness)

Peter Molnár – Introduction to Empirical Finance

Paolo Lacche – Product Management: innovating from startup to enterprise







Stephan Proksch


Stephan Proksch  is Mediator, Management Consultant and Trainer. He is  Partner of Trialogis  OG ( and coordinator of the mediation course of Incite of the Austrian Chamber of Commerce (WKO).  His specialization is mediation and business mediation, organizational development and team building.
He obtained a business degree from Wirschaftsuniversität Wien and a PhD degree from   IFF in Vienna (Organizational development) . He is author of the book Conflict Management (Springer International Publishing, Switzerland 2016).


Conflict Management and Mediation

Course in InSIS – 4EK 611, classroom – NB 457

The course covers the basics of conflict management and mediation in organizations. The participants will distinguish the most important methods and find out how  to apply them adequately. Additionally they  will learn how to act appropriately in conflict situations.

Course  syllabus

  • Basic conflict theory
  • Conflict analysis
  • Conventional and complementary forms of conflict management
  • Benefits and limits of presented methods
  • Basics of negotiation skills
  • Techniques of conflict management and mediation
  •  Conflict prevention
  • Reflection and analysis of one’s own behavioral patterns in conflict situations
  • Case analysis and role plays


Proksch, Stephan: Conflict Management. Springer International Publishing, Switzerland 2016.



Johannes Fürnkranz

CANCELLED (due to illness)

Johannes Fürnkranz is Professor for Knowledge Engineering at TU Darmstadt. He has studied at the Technical University Vienna, the University of Chicago,  and at Carnegie Mellon University. His research interests are in machine learning and data mining, in particular in preference learning, rule learning, multi-label classification, and their applications to game playing, web mining and the social sciences. He is a frequent member of program committees of relevant conferences, was co-chair of ECML/PKDD 2006, ICML 2010, and Discovery Science 2013, and serves as an action editor of “Machine Learning” and the editor-in-chief of the journal “Data Mining and Knowledge Discovery”.


Inductive Rule Learning

Course in InSIS – 4IZ 570, classroom – NB 458

Rules – the clearest, most explored and best understood form of knowledge representation – are particularly important for data mining,
because they offer the best tradeoff between human and machine understandability.

This course will present algorithms for automated rule learning and discovery as investigated in classical machine learning and modern data mining.

Course syllabus

  • Algorithms for learning single rules in propositional logic
  • Learning rule sets with the covering or separate-and-conquer algorithm
  • Inductive logic programming algorithms for learning rules in first-order logic
  • Discuss approaches that allow to make predictions in structured output spaces
  • Elementary data mining algorithms such as association rule discovery will also be covered, as well as essential concepts of
    machine learning and data mining.


Most of the course will follow the book “Foundations of Rule Learning”, that appeared in Springer-Verlag in early 2012.



Peter Molnár


Associate Professor RNDr. Ing. Peter Molnár PhD. is originally from Slovakia. He obtained a masters degree in physics from Charles University, Prague and masters degree in finance from University of Economics, Prague. Afterwards he moved to Norway. He obtained a PhD degree from Norwegian School of Economics, Bergen, Norway. Subsequently he worked at Norwegian University of Science and Technology, Trondheim, Norway and is currently employed at University of Stavanger, Norway.



Introduction to Empirical Finance

Course in InSIS – 4ST 640, classroom – SB 109

This course covers empirical and quantitative analyses of financial and commodity markets. With financial markets we mean stocks, currency, and bond markets. With commodity markets we mean energy, metals and agricultural markets.

Through the course, the students are expected to develop competence in conducting their own empirical analyses of asset prices. The course will consist of standard lecturing and practical exercises, interfacing econometric methods and theories and topics from finance and commodity market economics.

Course syllabus

  • Factor models – capital asset pricing model (CAPM), 3-factor model of Fama and French,  4-factor model of Carhart,  Other factor models
  • Principal component analysis – Introduction to PCA with some practical examples
  • Volatility modelling –  Time-varying volatility,  GARCH models, Realized volatility, Range-based volatility
  • Correlation – Introduction into correlation and why it matters
  • Cointegration – Introduction and examples
  • Copulas – Introduction and examples
  • Quantile regression – Introduction and examples


Alexander C., 2008, Market Risk Analysis – 4-volume set, Wiley. Lectures will be based mainly on Volume II, but obtaining this book is not necessary.



 Paolo Lacche

Paolo Lacchè is a Product Management leader with over 13 years of global experience. He has studied Product Management at the Haas School of Business, Berkeley, California and served as a Senior PM for industry leading organizations such as Hewlett-Packard, Microsoft and Skype, managing products used by millions of users worldwide and generating millions of dollars in revenue. Today Paolo Lacchè serves as business consultant for the main tech companies , as well as acting as mentor and advisor for several  startup accelerators.

Product Management: innovating from startup to enterprise

Course in InSIS – 4IT 470, classroom – RB 338

Understand the theory of what is product management and what are the best practice and go  through real industry examples and see how these practices are applied and what challenges they present. Look at the startup world and understand how innovation and new products see the light.


Course syllabus

  • Product management theory
  • Having a good understanding of the business: mission, vision and business model
  • Defining a product strategy
  • Creating and managing a product roadmap
  • Leadershipand influence in cross-functional teams
  • Creating and delivering effective presentations
  • The function of product management in a modern enterprise
  • How a real-life working day looks like for a product manager
  • Product management in a startup today
  • Common startup mistakes in product
  • Size and timing for a startup with regard toproduct development
  • Choosing the right tools
  • Product management in the literature and references