In this course we look at the problem of business process compliance.

Generally, business processes describe the working procedures within an organization. Still, organizations have to make sure that working procedures follows certain policies and regulations, i.e., compliance rules. Here, we study how to reason about the compliance of business processes with such compliance rules. We base our reasoning on temporal logic.

Processes are omnipresent in the healthcare domain. Patients, doctors, as well as nursing- and laboratory staff are involved in care pathways, but also supporting processes, such as logistics of drugs, play an important role. Requirements on healthcare providers with regards to quality, efficiency, and profitability grow continuously and require a strong process understanding to identify potentials for process improvements, innovations, and automation.

In this lecture, you will learn process modeling as a technique for the discovery, analysis, improvement, and automation of different healthcare processes (care pathways, standard operating procedures, supporting processes, etc.). We will introduce BPMN (Business Process Model and Notation) - the most widespread process modeling language in industry and research. Further, techniques to analyze and redesign healthcare processes will be presented. As decisions play a crucial role in healthcare, DMN (Decision Model and Notation) as a standard for decision modeling and management will be discussed.

This seminar will focus on the practical usability issues that emerge in designing privacy preserving algorithms to handle large high-dimensional datasets. Examples of such datasets emerge in the healthcare, education, and online marketing domains, where oftentimes datasets can be characterised by several describing attributes that are comparatively sparsely populated. Furthermore, in the light of current data privacy legislation, reports from statistical organisations such as Statistica, indicate that Internet users are very concerned about the disclosure of the sensitive personal data and the fact that such information can be exploited for identity theft. Platforms such as Identity-Leak Checker, bring to the fore the fact that these concerns are strongly grounded in that the risk of malicious players getting access to personal data grows with the number of applications (e.g. social media and personalised healthcare) using personal data to operate. As such we will consider usability from both the perspective of generating privacy preserving data to support data analytics operations, and methods of handling human-centered privacy issues.

Software applications have become an integral part of daily life, sharing information across devices pervasively and seamlessly to conduct and ever growing number of computing operations. One of the results of software

application ubiquity is the complexity of designing and maintaining these applications in ways that guarantee security in addition to reliability and availability. Main stream press examples of data and application breaches

such as the case of the MyFitnessPal security breach in 2018 that resulted in hackers acquiring the private data of more than 150 million users, underline the importance of secure design and coding. The goal of this course

therefore, is to learn how to identify, and prevent security vulnerabilities.


In order to achieve this, we will study the principles, methods, and approaches needed for the development of secure applications such as web, mobile, and classic applications. This will be achieved through a series of twice

weekly lectures during the winter semester, focused on studying methods of analysing software applications to identify and analyse vulnerability classes and corresponding attack vectors on a theoretical as well as practical


How can we make informed presumptions about the future, and why is this paramount, more than ever, in present times? This elementary question remains a pressing issue for start-ups, corporates, institutions, and our society to be able to respond to an increasingly volatile environment. ​
In this course, we will introduce you to the underlying principles of strategic technology foresight. Across the contexts of academia, entrepreneurship, companies, and policy, you will learn to strategically evaluate the disruptive potential of emerging digital technologies by employing state-of-the-art foresight methods.​
Following inputs from introductory lectures, hands-on exercises, and presentations from industry experts on foresight practice, you will work in project teams on a selection of innovative technologies developed at HPI throughout this course. You will gain in-depth knowledge for exemplary IT-based foresight tools such as scenario analysis or roadmapping which will enable you to contextualize and complement your data science expertise. By concluding this course, you will be able to understand the relevance and application opportunities of strategic foresight for technologies that will potentially shape our future.​