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 Bachelor’s and Master’s thesis that thematically match my research interests. If you are interested in one of the open topics or have an idea that is not listed here, feel free to contact me!

Please consult our theses page for more details and topics.

Open thesis topics
  • Currently no open topics. Contact me if you have a custom topic in mind.
Finished and ongoing theses
  • [Bachelor] Evaluating the Impact of Large Language Models on Coding and Theme Development in Qualitative Research
  • [Bachelor] Socio-Technical Challenges in Software Engineering
  • [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

Publications


2023

  • Alina Mailach and Norbert Siegmund. Socio-Technical Anti-Patterns in Building ML-Enabled Software: Insights from Leaders on the Forefront. In Proceedings of the International Conference on Software Engineering (ICSE), pages 690–702. IEEE, May, 2023. Acceptance rate: 26% (209 / 796). DOI: 10.1109/ICSE48619.2023.00067
    [paper][preprint][artifacts][poster]



Talks
  • 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)