Dr. Gunel Jahangirova

Assistant Professor

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Biography

Gunel Jahangirova is a Lecturer in Computer Science at King's College London. She received her PhD from a joint program between Fondazione Bruno Kessler in Trento, Italy, and University College London in the United Kingdom. Prior to joining King’s, she conducted postdoctoral research on an ERC advanced grant project titled 'Precrime' at Università della Svizzera italiana in Lugano, Switzerland. Her research interests encompass software testing, software engineering, artificial intelligence, and search-based software engineering, with a focus on empirical studies of fault localization techniques and deep neural networks. Gunel has contributed to various peer-reviewed articles and conference papers that highlight her expertise in hybrid quantum-classical software architectures, ethical autonomous decision-making, and genetic programming. She has co-authored multiple publications including those on the influence of AI in software development and methodologies for testing and verification. Gunel actively engages in research aimed at advancing the field of software engineering through innovative approaches and interdisciplinary collaboration.

Research Interests

Experience

Lecturer

— Present

King's College London • London, ENG

Teaching and conducting research in the Department of Computer Science, focusing on software testing and artificial intelligence.

Requirements for King's College London

Master Program
Requirements
GPA Requirement
Required:3.3
IELTS
Listening
Required:6.5
Reading
Required:6.5
Writing
Required:6.5
Speaking
Required:6.5
Overall
Required:7
TOEFL
Listening
Required:23
Reading
Required:23
Writing
Required:25
Speaking
Required:23
Total
Required:100
Prerequisites
Bachelor's degree in a relevant subject Quantitative competency (for some Economics/Finance programs)
Application Checklist
  • Official Transcripts
  • Personal Statement
  • Two Academic References
  • CV/Resume
  • English Language Proficiency Proof
Specialization Notes

Requirements are consistent across King's Business School and Social Science & Public Policy departments for standard Master's entries.