Alina Mailach

Leipzig University
Chair of Software Systems / ScaDS.AI
Augustusplatz 10
04109 Leipzig

Room:

Phone:

E-mail:
P622 (Paulinum)
D03.20 (Löhrs Carré)
+49 (0) 341 97 323 47 (Paulinum)

alina.mailach@informatik.uni-leipzig.de

Research Interest

With my interdisciplinary background in data/computer science and psychology, I am especially interested in understanding the vast variety of social and technical challenges that accompany the development of ML-enabled systems. Furthermore, I have a general interest in empirical methods and open and reusable research artifacts.

Thesis Supervision

I supervise undergraduate and graduate theses that are related to my research interests. If you are interested in my research directions and would like to write your thesis in my field, feel free to contact me!


NOTE: I will not be supervising Bachelor’s and Master’s theses again until July 2026. Only contact me if you want to start by then.

Finished and ongoing theses
  • [Master] KI-Code Assistenten und Produktivität von Softwareentwicklern: Eine industrielle Fallstudie
  • [Bachelor] Entwicklung eines Tools zur Unterstützung qualitativer Forschung mit Large Language Models
  • [Bachelor] Automatische Generierung von Visualisierungen basierend auf Datenflüssen in einer Microservice Architektur
  • [Bachelor] Fine-Tuning a Foundation Model for Qualitative Research
  • [Bachelor] Managing Prompt Engineering Experiments: Tools and User’s needs
  • [Bachelor] Qualitative Methods and Artifacts in Software Engineering Research
  • [Bachelor] Socio-Technical Challenges in Software Engineering

Publications

2026

2025

2024

2023



Talks
  • FSE 2026: Views on Internal and External Validity in Empirical Software Engineering: 10 Years Later and Beyond
  • ICSE 2026 (online): Views on Internal and External Validity in Empirical Software Engineering: 10 Years Later and Beyond
  • FSE 2025: ‚Ok Pal, We Have to Code That Now‘: Interaction Patterns of Programming Beginners with a Conversational Chatbot.
  • SE 2024: Socio-Technical Challenges and Recommendations for Mitigation in Building ML-Enabled Systems (Feb 26- Mar 1, 2024, Linz, Austria)
  • ICSE 2023: Socio-Technical Anti-Patterns in Building ML-Enabled Software (May 14-20, 2023, Melbourne, Australia)
  • FOSD 2023: Towards Reproducible and Reusable Artifacts in Performance Learning Experiments (March 27-31, 2023, Ulm, Germany)