Bio:

If language shapes our reality and we have the capacity to change our language, it is possible to ameliorate our world through a purpose-driven change of our language. Information systems occupy a dual role in this regard. First, they must depict domain concepts, which thereupon influence their use within the domain – a reciprocal effect. Second, they can provide technical support for the generation and evaluation of alternative concepts. The second role appears largely disregarded in the current literature. My research is centered around (i) formulating a research agenda for the Information Systems discipline which addresses the outlined aspects and (ii) investigating machine learning procedures that can support the generation of alternative concepts.

I recommend that bachelor and master students, who want to find a thesis topic in this field, consult literature of the following areas:

• Linguistic Relativity Principle
• Language-Action Perspective
• Concept Engineering & Concept Ethics
• Generative Language Models
• Contingency and Possible Worlds
• Text World Theory 

For literature advice or further questions conerning the formuluation of your thesis within the Information Systems discipline, I am happy to help. Furthermore, I offer to advise theses that can be broadly allocated in one of the following areas: artificial intelligence, machine learning, deep learning, data management, organizational problem-solving, and philosophy of information.

Curriculum Vitae:

Education

10/2015 - 04/2019: Business Information Systems, B. Sc., University of Duisburg-Essen

• Bachelor Project: "Design and Implementation of a Smart Contract-based Solution"
• Bachelor Thesis: "Design Thinking: Theoretical Background, Key Concepts, and Application Potentials in the Context of Software Development"

04/2019 - 05/2021: Business Information Systems, M. Sc., University of Duisburg-Essen

• Master Project: "Prototypical Development of an Accomodation App for Smart Urban Districts"
• Master Thesis: "Contingency Adaption Through Deep Learning: A Critical Reflection on the Applicability of Deep Learning for Organizational Problem-Solving"

Professional Positions

since 08/2021: Research Assistant (Wissenschaftlicher Mitarbeiter) at the Research Group for Information Systems and Enterprise Modelling, University of Duisburg-Essen

10/2019 - 07/2021: Student Assistant (Wissenschaftliche Hilfskraft) at the Research Group for Information Systems and Enterprise Modelling, University of Duisburg-Essen

03/2018 - 01/2020: Working Student in the area of Metadata Managament, Data Governance, and Data License Management at E.ON Digital Technology GmbH, Essen

07/2017 - 12/2017: Working Student in the area of Database Testing at Finanz-Informatik GmbH & Ko. KG, Münster

Publications:

• Frank, Ulrich; Maier, Pierre; Bock, Alexander: Low Code Platforms: Promises, Concepts and Prospects: A Comparative Study of Ten Systems - ICB Research Report, 70. Essen 2021. doi:10.17185/duepublico/75244) PDFFull textCitationAbstractDetails

  

  In recent years, the catchword “low‐code” has evolved into what can be seen as a major trend
  in software development platforms. A growing number of vendors respond to this trend by
  offering software development platforms that promise limited need for coding only and a tremendous
  boost in productivity. Both aspects have been the subject of intensive research over
  many years in areas such as domain‐specific modeling languages, model‐driven software development,
  or generative programming. Therefore, the obvious question is how ʺlow codeʺ
  platforms differ from such approaches and what specific performance features they offer.
  Since there is no unified definition of “low‐code”, the only way to develop an elaborate understanding
  of what it is – and might be – is to analyze the actual use of the term. For obvious
  reasons, it is not promising in this respect to rely on marketing announcements made by vendors.
  Instead, it seems more appropriate to examine “low‐code” platforms. This research report
  presents a study of 10 relevant platforms, capturing and assessing common characteristics
  as well as specific features of individual tools. The study is guided by a method that consists
  of a conceptual framework, which provides a uniform structure to describe and compare “lowcode”
  platforms, and a process model that describes the sequence of steps.

Tutored Theses:

• Metadata-enhanced Data Warehousing: Conceptions and Contributions to Data Integration (Bachelor Thesis Business Information Systems, in progress)
• Business Process Automation through Robotic Process Automation? Critical Analysis and Synthesis of existing Criteria Catalogs for the Identification and Selection of eligible Business Processes (Bachelor Thesis Business Information Systems, 2022)
• Data Governance: Reconstruction of key concepts and analysis of implementation using existing enterprise modeling approaches (Bachelor Thesis Business Information Systems, 2022)
• Convolutional Neural Networks: Technical Foundations and Critical Evaluation of their Use in Organisations (Bachelor Thesis Business Information Systems, 2022)
• XAI Approaches from the Perspective of Legal Requirements: Design and Use of an Evaluation Frame (Bachelor Thesis Business Information Systems, 2022)
• Action-theoretic Perspective: A Beneficial Extension for Enterprise Modeling? (Bachelor Thesis Business Information Systems, 2022) AbstractDetails

  Motivation:

  Viele Faktoren beeinflussen, welche Handlungen von Individuen in

  Unternehmen ausführt werden und zu welchem Zeitpunkt die Ausführung der

  Handlung ausgelöst wird. Dabei spielen insbesondere vorgegebene

  Entscheidungskriterien, die vorliegende Umweltsituation und die

  persönlichen Wahrnehmungen bzw. Einschätzungen der Individuen eine

  zentrale Rolle.

  Im Rahmen dieser Arbeit ist zunächst zu untersuchen, wie das genaue

  Zusammenspiel der genannten Faktoren abläuft und welche weiteren

  Faktoren dabei beteiligt sind. Innerhalb der BWL und der

  Organisationstheorie existieren dazu verschiedene Handlungstheorien, die

  vom Autor zu erläutern und gegenüberzustellen sind.

  Nach der begründeten Auswahl einer der Handlungstheorien ist zu

  analysieren, inwiefern die für Handlungsauswahl und -auslösung

  relevanten Faktoren in Unternehmensmodellen berücksichtigt werden

  können. Existierende Sprachen zur Unternehmensmodellierung fokussieren

  typischerweise auf die Abbildung von Organisationsstrukturen und

  Geschäftsprozessen. Es ist daher herauszuarbeiten, für welche der

  ermittelten Faktoren in einer ausgewählten Modellierungssprache bereits

  Konzepte vorhanden sind und welche Konzepte noch ergänzt werden müssten.

  Ein Ausblick auf verschiedene Gestaltungsmöglichkeiten bei der

  Einführung der zusätzlichen Konzepte soll den Abschluss der Arbeit

  bilden.

• In-Memory Databases: Technical and Conceptual Foundations and Comparison of Selected Systems (Bachelor Thesis Business Information Systems, 2022) AbstractDetails

  In den letzten Jahren haben sog. "In-Memory"-Datenbanken (IMD) an Bedeutung gewonnen. Sie versprechen einerseits eine gemeinsame Repräsentation von Daten für OLTP und OLAP, wodurch der in DWS erforderliche Transformationsaufwand entfällt und die Datenaktualität deutlich gesteigert wird. Gleichzeitig ermöglichen sie eine höhere Performanz von Analyseverfahren. Diesen möglichen Vorteilen steht eine Reihe von Herausforderungen gegenüber. In dieser Bachelorarbeit sollen zunächst die wesentlichen Architekturkonzepte von IMD untersucht werden. Anschließend ist zu analysieren, wie die Integration mit Anwendungssystemen erfolgt. Vor diesem Hintergrund sind Anforderungen an IMD zu analysieren. Abschließend sind auf dieser Grundlage ausgewählte IMD (bspw. Open Source Systeme) zu vergleichen.

• Use of Machine Learning in the Manufacturing Industry: Design of a Method for the Identification and Selection of Application Possibilities (Master Thesis Business Information Systems, 2022)
• Customer Churn Prediction in Literature and Practice - Design of a Process Model for the Selection of a Churn Prediction Model in Contractual Settings (Bachelor Thesis Business Information Systems, 2022)
• Problem structuring methods in requirements engineering – Development of a suitability framework for use in requirements elicitation (Bachelor Thesis Business Administration, 2022)
• Deep Learning in Organizations: Development and Application of an Evaluation Framework for the Comparison of Explainable Artificial Intelligence Methods (Bachelor Thesis Business Information Systems, 2022)