Scholar
Gül Calikli
Google Scholar ID: lShgfvwAAAAJ
Associate Professor in Software Engineering, School of Computing Science, University of Glasgow
Citations & Impact
Citations
715
H-index
15
i10-index
18
Publications
20
Co-authors
0
Resume
Academic Achievements
- September 2025: Invited to serve on the Editorial Board as an Associate Editor for the ACM Transactions on Software Engineering and Methodology (TOSEM).
- August 2025: Promoted to Associate Professor (Senior Lecturer) in Software Engineering. Also invited to serve at the Programme Committee of ICPC 2026 (Research Track).
- July 2025: Paper 'Perspectives, Needs and Challenges for Sustainable Software Engineering Teams: A FinServ Case Study' accepted at ESEM 2025.
- June 2025: Invited to serve at the Programme Committee of FSE 2026 (Research Papers Track).
- May 2025: Invited to serve at the Programme Committee of MSR 2026 (Technical Papers Track).
- January 2025: Paper 'Impact of Request Formats on Effort Estimation: Are LLMs Different than Humans?' accepted at FSE 2025.
- December 2024: Invited to serve at the Programme Committee of ICSE 2026 (Research Track).
- December 2024: Paper 'A Laboratory Experiment on Using Different Financial-Incentivization Schemes in Software-Engineering Experimentation' accepted to be published at PeerJ Computer Science Journal.
- October 2024: Invited to serve at the EPSRC Peer Review College.
- June 2024: Paper 'Guidelines for Using Financial Incentives in Software Engineering Experimentation' accepted to be published at Empirical Software Engineering Journal.
- May 2024: Paper 'Virtual Platform: Effective and Seamless Variability Management for Software Systems' accepted to be published at IEEE Transactions on Software Engineering Journal.
Research Experience
- Before joining the University of Glasgow, she was a senior researcher at the Department of Informatics, University of Zurich (UZH), Switzerland.
Education
- Ph.D. in Computer Engineering from Boğaziçi University, Istanbul.
Background
- Her research field is empirical software engineering with a focus on human aspects (cognitive and social psychology) accompanied by Data Analytics and Machine Learning. Her vision is to enhance software practitioners’ decision-making to improve software quality by developing (1) tools and techniques based on cognitive psychology; and (2) ML systems (e.g., LLMs) with human in the loop that can be regarded as a joint cognitive system.
Miscellany
- Looking for self-motivated students with strong programming skills (e.g., Java, Python, C++, etc.) and background in statistical analysis and Machine Learning (e.g., Deep Learning, NLP, LLMs). Industrial or open-source software development experience is desirable.