Humboldt-Universität zu Berlin - Faculty of Mathematics and Natural Sciences - Process Management and Information Systems

General Information

Our team offers bachelor and master thesis topics as well as student projects to be written in English. 

Student may apply for a thesis or a study project during within two application windows in a year, in which new topics are made available. The first window is open from February 1st until April 1st. The second window is open from July 1st until October 1st.

Here you can find the information on how to write a thesis with us. Slides are available here (part I, part II), and recordings here (part I, part II). 

Furthermore, find below a summary of guidelines for working on your thesis with us.

Expression of Interest in a Topic (Thesis or Study Project)

If you are interested in one of the topics, please fill in the application form.

Address your application to Dr. Saimir Bala and please explain why this topic is interesting for you and how it fits your prior studies. Also explain what are your strengths in your studies and in which semester of your studies you are.

Application process overview

• There are two main time windows in which the team proposes new topics: Feb 1st ­– Apr 1st and Jul 1st – Oct 1st
• Within these windows students can apply for an open topic (see list of open topics below)
• Application is done by filling in the application form.
• We collect your applications and make a topic-student assignment in two rounds. First round on March, second round after the deadline. For the winter session, we have two rounds (Sep, Oct).
• Once a student has been matched to a supervisor, a kick-off meeting is scheduled to scope the topic.
• Then, students must submit a research proposal to the supervisor within a month.
• If the proposal is graded as passed, the supervision is officially registered.
• Once the thesis work is concluded, the thesis defense is scheduled within a dedicated defense slot.

Important Dates

23.01.2025: New topics released. Students can express their interest.

06.02.2025: Topic assignment (1st round)

07.03.2025: Topic assignment (2nd round)

01.04.2025: Expression of interest deadline

04.04.2025: Topic assignment (3rd round)

Milestones:

- Kick-off: shortly after assignment round

- Research proposal submission deadline first round (1 month after official kick-off)

- Official start (if proposal sufficient)

- Thesis delivery 

- Grading & Defence

Formatting and Delivery of the Manuscript

Please consider the following hints and guidelines for working on your thesis:

• Templates for thesis and proposal: https://www.informatik.hu-berlin.de/de/studium/formulare/vorlagen
• In addition a list of aids used (more details below) must be included after the declaration of authorship
• Page limits are as follows
• page limit is for Bachelor Informatik 40 pages and for Kombibachelor Lehramt Informatik 30 pages
• page limit is for Master Informatik 80 pages and for Master Information Systems 60 pages
• The limits do not include cover, table of content, references, and appendices.

List of aids used*

As generative AI tools evolve, it is important to clearly declare all the tools and aids used in your thesis work to ensure transparency in presenting your personal performance. Such transparency also acts as an important safeguards against accusations of academic fraud.

All aids must therefore be reported in the form of a table, accompanied by a signed declaration of “list of aids used”. Such table is required even in cases where no aids were used.

This table must be placed behind the authorship declaration in a separate page in the thesis and must include at least the following columns

• aids/tools used – which tools was a used (e.g., ChatGPT, Deepl, Gemini, etc)
• type(s) of use – explaining what was its use (e.g., ChatGPT was used to improve the writing style, limited to editing)
• affected areas/chapters – where are the results of tools affecting the thesis (e.g., chapter "Research methodology" p. 15 – 18)
• documentation of the tool – a link to the documentation of the tool (e.g., link to ChatGPT's help page)

Finally, below is an example of a signed declaration that must follow the list of aids table.

We hope that this will help increasing transparency and protect you against academic fraud. 

* Credits to WU Vienna

Preliminary references

The candidate is expected to be familiar with the general rules of writing a scientific paper. Some general references are helpful for framing any thesis, no matter which topic:

• Wil van der Aalst: How to Write Beautiful Process and Data Science Papers? Archive Report (2022).
• Jan Recker: Scientific Research in Information Systems: A Beginner's Guide . Springer, Heidelberg, Germany (2021).
• Jan Mendling, Benoit Depaire, Henrik Leopold: Methodology of Algorithm Engineering. Archive Report (2023).
• Claes Wohlin, Pär Runeson, Martin Höst, Magnus Ohlsson, Björn Regnell, Anders Wesslén Experimentation in software engineering . Springer Science & Business Media (2012).
• Ken Peffers, Tuure Tuunanen, Marcus A. Rothenberger, Samir Chatterjee: A Design Science Research Methodology for Information Systems Research . J of Management Information Systems 24(3): 45-77 (2008).
• Barbara Kitchenham, Rialette Pretorius, David Budgen, Pearl Brereton, Mark Turner, Mahmood Niazi, Stephen G. Linkman: Systematic literature reviews in software engineering - A tertiary study . Information & Software Technology 52(8): 792-805 (2010).
• Lagendijk, Ad. Survival Guide for Scientists: Writing, Presentation, Email . Amsterdam University Press (2008).
• Adam LeBrocq: Journal of the Association for Information Systems Style Guide.  https://aisel.aisnet.org/cais/cais_style_guide.pdf

In agreement with the supervisor an individual list of expected readings should be studied by the student in preparation of the actual work on the thesis.

Grading

The grading of the thesis takes various criteria into account, relating both to the thesis as a product and the process of establishing its content. These include, but are not limited to:

• Correctness of spelling and grammar
• Aesthetic appeal of documents and figures
• Compliance with formal rules
• Appropriateness of thesis structure
• Coverage of relevant literature
• Appropriateness of research question and method
• Diligence of own research work
• Significance of research results
• Punctuality of work progress
• Proactiveness of handling research progress

Recent Topics

The following topics are available within the current application window.

Topic 1: Process Inventory Visualization (Bachelor/Master) 

Description: A part of Process Mining focuses on the discovery of process models from event data. In order to support monitoring on topic, capabilities are needed that not only show the process model itself, but also the inventory of cases running through the process. Research problem: So far, process mining has missed the opportunity to systematically show the current state and the speed of the cases running through the process. The aim of this thesis is to develop a corresponding visualization concept and prototypically implement it for complex event data that is available in graph databases such as Neo4j. 

Initial references:

• Waibel, P., Pfahlsberger, L., Revoredo, K., & Mendling, J. (2022). Causal process mining from relational databases with domain knowledge. arXiv preprint arXiv:2202.08314.
• Chen, W., Guo, F., & Wang, F. Y. (2015). A survey of traffic data visualization. IEEE Transactions on intelligent transportation systems, 16(6), 2970-2984. 

Supervisor: Jan Mendling

Topic 2: SQL Database Obfuscation (Bachelor/Master) 

Description: Databases play an important role as data sources for process mining. A key challenge is making such databases available for research, because private or secret information must not be disclosed. Research problem: So far, there are different tools available that can help to anonymize or obfuscate information in databases. The aim of this research is to systematically analyze the capabilities of existing tools and requirements of sharing databases for process mining. Based on this analysis, a tool will be developed that is able to generate a synthetic database with load data in such a way that private information is obfuscated, but structural properties of the process-related data are preserved. 

Initial references:

• Majeed, A., & Lee, S. (2020). Anonymization techniques for privacy preserving data publishing: A comprehensive survey. IEEE access, 9, 8512-8545.
• Li, G., de Murillas, E. G. L., de Carvalho, R. M., & Van Der Aalst, W. M. (2018). Extracting object-centric event logs to support process mining on databases. In Information Systems in the Big Data Era: CAiSE Forum 2018, Tallinn, Estonia, June 11-15, 2018, Proceedings 30 (pp. 182-199). Springer International Publishing. 

Supervisor: Jan Mendling

Topic 3: Process Baselining (Bachelor/Master) 

Description: Process improvement has to build on a solid understanding of a process and the infrastructure that supports it. This is particularly important for assessing the baseline cost of the process and options for improvement. Research problem: So far, process mining research has focused by and large on the analysis of duration. The aim of this research is to develop a cost model for processes that defines all the relevant cost factors. Based on this cost model, the candidate will develop an analysis technique that makes estimations of cost based on event log data. 

Initial references:

• Sampathkumaran, P. B. (2013). Computing the cost of business processes (Doctoral dissertation, LMU München).
• Vergidis, K., Tiwari, A., Majeed, B., & Roy, R. (2007). Optimisation of business process designs: An algorithmic approach with multiple objectives. International Journal of Production Economics, 109(1-2), 105-121. 

Supervisor: Jan Mendling

Topic 4: Enhancing Human-AI Co-Creativity: Investigating Generative AI Tools as Creative Collaborators (Master) 

Description: The rise of generative AI tools, such as ChatGPT, DALL·E, and MidJourney, has opened new frontiers in collaborative creativity, where AI systems contribute to human creative processes. This thesis investigates the evolving role of generative AI as a creative partner – more than a tool, less than a human collaborator. GenAI tools can support ideation, problem-solving, and refinement across various creative domains. The study can take different directions, from systematically analyzing and structuring the “creative competencies” of generative AI tools to studying how users collaborate with generative AI in real-world creative tasks. Through surveys, user studies, and evaluations of creative outputs, this research aims to uncover human-AI co-creativity’s mechanisms, challenges, and opportunities. The findings will provide a deeper understanding of how AI can enhance creativity while highlighting potential barriers to effective collaboration. 

Initial references:

• Davis, N. (2013). Human-Computer Co-Creativity: Blending Human and Computational Creativity. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 9(6):9–12.
• Haase, J., & Pokutta, S. (2024). Human-AI Co-Creativity: Exploring Synergies Across Levels of Creative Collaboration (arXiv:2411.12527). arXiv. https://doi.org/10.48550/arXiv.2411.12527
• Heyman, J. L., Rick, S. R., Giacomelli, G., Wen, H., Laubacher, R., Taubenslag, N., ... & Malone, T. (2024, June). Supermind Ideator: How scaffolding Human-AI collaboration can increase creativity. In Proceedings of the ACM Collective Intelligence Conference (pp. 18-28). 

Supervisor: Jennifer Haase

Topic 5: Exploring the Phenomenon of AI Companions and Virtual Girlfriends: Understanding Human Attachment to Digital Partners (Master) 

Description: With the rise of AI-driven virtual companions and “AI girlfriends” in apps like Replika, a new dimension of human-computer interaction is emerging, blurring the lines between emotional connection and digital simulation. This thesis seeks to explore the psychological, social, and technological aspects of these AI companions. Key questions include: What motivates individuals to seek relationships with AI partners? How do users form attachments to non-human entities? What role does personalization and anthropomorphism play in fostering these connections? By employing web searches, qualitative interviews, surveys, or case studies, this research will aim to uncover the broader implications of AI companions on social behavior, emotional well-being, and the evolving nature of human entanglement with GenAI tools. 

Initial references:

• Chaturvedi, R., Verma, S., Das, R., & Dwivedi, Y. K. (2023). Social companionship with artificial intelligence: Recent trends and future avenues. Technological Forecasting and Social Change, 193, 122634. https://doi.org/10.1016/j.techfore.2023.122634
• Dang, J., & Liu, L. (2023). Do lonely people seek robot companionship? A comparative examination of the Loneliness–Robot anthropomorphism link in the United States and China. Computers in Human Behavior, 141, 107637. https://doi.org/10.1016/j.chb.2022.107637
• Strohmann, T., Siemon, D., Khosrawi-Rad, B., & Robra-Bissantz, S. (2023). Toward a design theory for virtual companionship. Human–Computer Interaction, 38(3–4), 194–234. https://doi.org/10.1080/07370024.2022.2084620 

Supervisor: Jennifer Haase

Topic 6: Anthropomorphic Perceptions of Large Language Models: what is the gender of ChatGPT and its Counterparts? (Bachelor/Master)

Description: In today's digital era, Large Language Models (LLMs) like ChatGPT are transforming the way we interact with technology, often blurring the boundaries between machine and human cognition. This thesis delves into the intriguing realm of anthropomorphism, the human tendency to attribute human-like qualities to non-human entities. Specifically, this research aims to uncover laypeople's underlying beliefs and implicit conceptions about ChatGPT and similar models concerning an implicit gender attribution. By designing and conducting a survey, the thesis will gain insights into individuals' perception of these cutting-edge technologies. The findings can potentially illuminate not only our relationship with LLMs but also the broader implications of human-machine interactions in an increasingly AI-driven world.

Initial References:

• Deshpande, A., Rajpurohit, T., Narasimhan, K., & Kalyan, A. (2023). Anthropomorphization of AI: Opportunities and Risks (arXiv:2305.14784). arXiv. https://doi.org/10.48550/arXiv.2305.14784
• Farina, M., & Lavazza, A. (2023). ChatGPT in society: Emerging issues. Frontiers in Artificial Intelligence, 6. https://www.frontiersin.org/articles/10.3389/frai.2023.1130913
• Aşkın, G., Saltık, İ., Boz, T. E., & Urgen, B. A. (2023). Gendered Actions with a Genderless Robot: Gender Attribution to Humanoid Robots in Action. International Journal of Social Robotics, 15(11), 1915–1931. https://doi.org/10.1007/s12369-022-00964-0

Supervisor: Jennifer Haase

Topic 7: Navigating Process Models with Semantic Zoom (Bachelor/Master)

Description: Semantic zoom enables users to seamlessly navigate between different levels of detail in complex data visualizations. While this concept is widely used in modern geographic navigation tools like Google Maps, it has not yet been applied in the process mining literature. This thesis aims to design a process model layout method based on semantic zoom principles and develop a prototype to test its effectiveness.

What You’ll Gain (and Who Should Apply):

• Gain: Proficiency in data visualization, process mining, and prototyping.
• Profile: Ideal for students interested in data visualization and layout strategies with min. basic programming skills (e.g., Python, Javascript)

Where to Start:

• Receive an idea of how semantic zoom works: V. Wiens, S. Lohmann, and S. Auer, “Semantic Zooming for Ontology Graph Visualizations,” in *Proceedings of the Knowledge Capture Conference, K-CAP 2017, Austin, TX, USA, December 4-6, 2017*, 2017, p. 4:1-4:8. Available: https://doi.org/10.1145/3148011.3148015.
• Another paper on semantic zoom: G. D. Carlo, P. Langer, and D. Bork, “Advanced visualization and interaction in GLSP-based web modeling: realizing semantic zoom and off-screen elements,” in *Proceedings of the 25th International Conference on Model Driven Engineering Languages and Systems, MODELS 2022, Montreal, Quebec, Canada, October 23-28, 2022*, 2022, pp. 221–231. Available: https://doi.org/10.1145/3550355.3552412.
• Understand the connection between geographic information and process mining: M. Syafiq, S. Azri, and U. Ujang, “Navigating Immovable Assets: A Graph-Based Spatio-Temporal Data Model for Effective Information Management,” *ISPRS International Journal of Geo-Information*, vol. 13, no. 9, 2024. Available: https://doi.org/10.3390/ijgi13090313.

Supervisor: Christoffer Rubensson

Topic 8: Enhancing Process Models with Contextual Information (Bachelor/Master)

Description: Analyzing healthcare processes involves considering multiple attributes across various patient groups. While current context-based process analysis tools address this requirement, they often lack adequate visual representation. This thesis aims to create a method for enhancing a process model with context-based variant information in healthcare and develop a prototype to test its effectiveness.

What You’ll Gain (and Who Should Apply):

• Gain: Proficiency in data visualization, process analysis, and prototyping.
• Profile: Ideal for students interested in data visualization and layout strategies, with basic programming skills (e.g., Python, Javascript) and curiosity in the healthcare domain.

Where to Start:

• Explore an approach for mining context-based variants: Rubensson, C., Mendling, J., Weidlich, M. (2024). Variants of Variants: Context-Based Variant Analysis for Process Mining. In: Guizzardi, G., Santoro, F., Mouratidis, H., Soffer, P. (eds) Advanced Information Systems Engineering. CAiSE 2024. Lecture Notes in Computer Science, vol 14663. Springer, Cham. Available: https://doi.org/10.1007/978-3-031-61057-8_23.
• Explore a different context-based variant analysis approach that is specialized in healthcare data: J. Cremerius, H. Patzlaff, V. Rahn, and H. Leopold, “Data-Based Process Variant Analysis,” presented at the Proceedings of the Annual Hawaii International Conference on System Sciences, 2023, pp. 3255–3264. Available: https://www.researchgate.net/publication/366920749_Data-Based_Process_Variant_Analysi
• Receive an overview of process enhancement: M. de Leoni, “Foundations of Process Enhancement,” in *Process Mining Handbook*, 2022, pp. 243–273. Available: https://doi.org/10.1007/978-3-031-08848-3_8.

Supervisor: Christoffer Rubensson

Topic 9: Artificial Intelligence in Project Management for Software Development Projects (Bachelor / Master)

Motivation & problem: Artificial intelligence is applied in software engineering management for taking decisions, estimating, managing technical debt, and planning, just to provide some examples. These applications have been widely studied by researchers. However, there is no study that presents a deep overview of how artificial intelligence is used for management activities in software development projects. Given the rising interest in artificial intelligence and the need of optimizing management in software projects, having a holistic overview can potentially be beneficial for practitioners and researchers.

Objectives: conduct a systematic review of the literature to identify the status quo on the topic. The findings shall be evaluated from the perspective of practitioners. The results shall be used to provide a framework that supports project managers of software development projects.

Prerequisites: (1) Basic knowledge of project management for software development projects; (2) Intermediate knowledge of artificial intelligence; (3) Pro-activity, self-organization, attention to detail (desirable).

Initial references:

• Perkusich, Mirko, et al. "Intelligent software engineering in the context of agile software development: A systematic literature review." Information and Software Technology 119 (2020): 106241.
• Kotti, Z., Galanopoulou, R., & Spinellis, D. (2023). Machine learning for software engineering: A tertiary study. ACM Computing Surveys, 55(12), 1-39.
• Fridgeirsson, Thordur Vikingur, et al. "An authoritative study on the near future effect of artificial intelligence on project management knowledge areas." Sustainability 13.4 (2021): 2345.

Supervisor: Cielo Gonzáles Moyano

Topic 10: Collaborative business-model-driven tool for agile software development projects (Bachelor / Master)

Motivation & problem: Agile software development methodologies and frameworks have changed the way software is created and are widely supported and used. However, this does not mean there are no challenges that jeopardize the principles of agile methodologies, increasing the failure rate of agile software development projects. This situation highlights the need for cohesive solutions. The use of business process models in the agile software development context emerges as a promising option due to their ability to facilitate communication and share knowledge.

Objectives: analyze, design, implement and evaluate a collaborative business-model-driven tool for agile software development projects. The objectives will be adapted to align the study goals of the student.

Prerequisites: (1) Knowledge of agile software development methodologies; (2) Knowledge of business process models; (3) Knowledge in frontend (e.g., JavaScript and TypeScript); (4) Knowledge in Java; (5) Knowledge in databases (e.g., PostgreSQL, mongoDB); (6) Pro-activity and self-organization.

Initial references:

• Moyano, Cielo González, et al. "Uses of business process modeling in agile software development projects." Information and Software Technology 152 (2022): 107028.
• Trkman, Marina, Jan Mendling, and Marjan Krisper. "Using business process models to better understand the dependencies among user stories." Information and software technology 71 (2016): 58-76

Supervisor: Cielo Gonzáles Moyano

Topic 11: Challenges faced by companies regarding the migration to post-quantum cryptography (PQC) and initial solution approaches (Bachelor/Master)

Description: Since quantum computers will be able to decrypt currently used cryptography, companies need to take action in order to keep their cryptography safe. One solution to be safe against quantum computer attacks is to migrate to post-quantum cryptography (PQC). However, exchanging current cryptography is not a trivial problem. There are several challenges companies have to face, which need to be explored further, as well as initial solution approaches. This thesis focuses more on the organizational perspective than on the technical one.

Initial references:

• Kvanutmszámítástechnika, A. (2021). The impact of quantum computing on IT security. Safety and Security Sciences Review, 3(4), 25–37.
• Scholten, T. L., Williams, C. J., Moody, D., Mosca, M., Hurley, W., Zeng, W. J., Troyer, M., & Gambetta, J. M. (2024). Assessing the Benefits and Risks of Quantum Computers (Version 2). arXiv. https://doi.org/10.48550/ARXIV.2401.16317
• Mashatan, A., & Turetken, O. (2020). Preparing for the Information Security Threat from Quantum Computers. MIS Quarterly Executive, 19(2), 157–164. https://doi.org/10.17705/2msqe.00030

Supervisor: Jennifer Brettschneider

Topic 12: Efforts in Germany regarding the migration to post-quantum cryptography (PQC) (Bachelor/Master)

Description: Since quantum computers will be able to decrypt currently used cryptography, companies need to take action in order to keep their cryptography safe. One solution to be safe against quantum computer attacks is to migrate to post-quantum cryptography (PQC). However, exchanging current cryptography is not a trivial problem. There are several challenges companies have to face. One of the challenges is that companies depend on their software provider or need e.g. hardware, software, and other services, to migrate to PQC. This thesis aims to explore the initiatives and offers available in and made by Germany to migrate to PQC. Specifically, the following areas can be examined: current offers from start-ups and established companies, government-funded projects, migration recommendations from the government, learning about needed competencies in companies through analyzing job advertisements by text mining techniques, etc.

Initial references:

• Kvanutmszámítástechnika, A. (2021). The impact of quantum computing on IT security. Safety and Security Sciences Review, 3(4), 25–37.
• BSI. (2022). Quantum-safe cryptography—Fundamentals, current developments and recommendations. Federal Office for Information Security. https://www.bsi.bund.de/SharedDocs/Downloads/EN/BSI/Publications/Brochure/quantum-safe-cryptography.pdf?__blob=publicationFile&v=6
• https://quantum-safe.ca/wp-content/uploads/2022/02/GACG-Quantum-Safe-Cybersecurity-Talent-and-Job-Market-Analysis-Final-Report.pdf
• https://www.bsi.bund.de/SharedDocs/Downloads/DE/BSI/Krypto/Marktumfrage_Kryptografie_Quantencomputing.pdf?__blob=publicationFile&v=10
• Müller, O., Schmiedel, T., Gorbacheva, E., & Vom Brocke, J. (2016). Towards a typology of business process management professionals: Identifying patterns of competences through latent semantic analysis. Enterprise Information Systems, 10(1), 50–80. https://doi.org/10.1080/17517575.2014.923514

Supervisor: Jennifer Brettschneider

Topic 13: Event Log Privacy Auditing (Master)

Description: Event Logs are often anonymized to ensure privacy. Most anonymization algorithms use formal privacy guarantees such as differential privacy. The issue with these techniques is that the algorithm or implementation could contain errors. Consequently, anonymized event logs might not have the targeted privacy guarantee and the individuals involved in the dataset might have a higher privacy loss than expected. Differential Privacy Auditing allows to check if an algorithm fulfils the differential privacy guarantee. The aim of this thesis is to adjust know Differential Privacy Auditing techniques to Event Log Anonymization and evaluate anonymization techniques from the process mining domain.

Initial references:

• Stephan A. Fahrenkrog-Petersen, Martin Kabierski, Han van der Aa, Matthias Weidlich:
  Semantics-aware mechanisms for control-flow anonymization in process mining. Inf. Syst.114: 102169 (2023)
• https://research.google/blog/dp-auditorium-a-flexible-library-for-auditing-differential-privacy/

Supervisor: Stephan Fahrenkrog-Petersen

Topic 14: Evaluating Fairness in Business Processes: A Manual Measurement Framework (Bachelor/Master)

Description: Understanding and ensuring fairness in business processes is essential for enhancing equity and mitigating bias. This study introduces a manual measurement framework for evaluating fairness in business processes. The framework focuses on systematically identifying and analyzing fairness-related metrics across diverse process stages, enabling practitioners to assess potential disparities and enhance equitable outcomes. The research offers practical insights and contributes to the growing field of fairness-aware business process management.

Initial references:

• Pohl, T., Qafari, M. S., & van der Aalst, W. M. (2022, October). Discrimination-aware process mining: A discussion. In International Conference on Process Mining (pp. 101-113). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-27815-0_8
• Muskan, M., Mannhardt, F., van Dongen, B.: Extending genetic process discovery to reveal unfairness in processes. In: Process Mining Workshops, Springer Nature Switzerland, Cham (2025)
  Adams, J. N., Ziegler, J., McDermott, M., Douglas, M. J., Eber, R., Gichoya, J. W., ... & Celi, L. A. (2024). A health equity monitoring framework based on process mining. PLOS Digital Health, 3(8), e0000575. https://doi.org/10.1371/journal.pdig.0000575
• Amico, B., Combi, C., Dalla Vecchia, A., Migliorini, S., Oliboni, B., & Quintarelli, E. Enhancing BPMN models with ethical considerations.

Supervisor: Rachmadita Andreswari

Topic 15: Establishing Fairness Benchmarks for Business Process Analysis (Master) 

Description: Benchmarking fairness metrics is a critical step in creating equitable and transparent business processes. This research proposes a comprehensive methodology for establishing fairness benchmarks, providing organizations with tools to evaluate their processes against standardized fairness criteria. The study emphasizes the importance of benchmarks in identifying systemic biases and guiding efforts to improve fairness in decision-making and operational workflows.

References:

• Amico, B., Combi, C., Dalla Vecchia, A., Migliorini, S., Oliboni, B., & Quintarelli, E. Enhancing BPMN models with ethical considerations.
• Pessach, D., & Shmueli, E. (2022). A review on fairness in machine learning. ACM Computing Surveys (CSUR), 55(3), 1-44. https://doi.org/10.1145/3494672
• Peeperkorn, J., & De Vos, S. (2024). Achieving Group Fairness through Independence in Predictive Process Monitoring. arXiv preprint arXiv:2412.04914.

Supervisor: Rachmadita Andreswari

Topic 16: Zero-shot learning for process prediction (Bachelor/Master)

• Wei Wang, Vincent W. Zheng, Han Yu, and Chunyan Miao. 2019. A Survey of Zero-Shot Learning: Settings, Methods, and Applications. ACM Trans. Intell. Syst. Technol. 10, 2, Article 13 (March 2019), 37 pages. https://doi.org/10.1145/3293318
• A systematic approach for learning imbalanced data: enhancing zero-inflated models through boosting, Yeasung Jeong, Kangbok Lee, Young Woong Park, Sumin Han, machine learning, 2024