Adekunle A. Ajibode
My expertise lies in utilizing Data Mining techniques to address research inquiries in various domains such as Software Engineering, Education, and Health Care. The majority of my Data Mining research replication packages are accessible on both my Bitbucket and GitHub profiles, while other Research replication packages specific to Software Engineering can be found solely on my GitHub profile. Additionally, all my published papers are freely available on several academic platforms, including Google Scholar and ResearchGate, as well as other libraries. Outside academics and research, I am seeking a position as an IT support specialist, Technical support specialist, IT technician, or a similar role where I can apply my technical skills, problem-solving abilities, and strong customer service orientation to effectively assist users with their IT needs.
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About me
Ajibode Adekunle is currently a PhD student in the Department of Computer Science at Queen's University, Kingston, Canada, specializing in optimizing the release management of Natural Language Processing models. He is conducting his research in the Maintenance, Construction and Intelligence of Software/Software Analysis and Intelligence Lab (MCIS/SAIL) under the supervision of Professor Bram Adams.
He earned his Master's degree from the Department of Computer Science and Technology in the School of Information Science and Technology at Zhejiang Sci-Tech University, Hangzhou City, Zhejiang Province, China, under the supervision of Professor Shu Ting. His MSc thesis is titled "Spectrum-based Fault Localization Method Using Formulas Combination."
He received his BSc(Ed) in Computer Science from Tai Solarin University of Education, Ijagun, Ijebu Ode, Nigeria, under the supervision of Dr. Ogunyinka in 2014.
Ajibode also holds a Nigerian Certificate in Education, a teacher's training certificate in Computer Science and Mathematics from the Federal College of Education, Osiele, Abeokuta, Ogun State, Nigeria.
He has been a teacher since 2005 and has mentored many students at the pre-school, high school, and post-secondary school levels.
Research Interest
My research focuses on various aspects of Software Engineering, particularly in:
- Language Model Releases
- Release Engineering of AI Models
- Repository Mining for Improving AI Model Releases
Publications
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A. A. Ajibode, T. Shu and Z. Ding, “Evolving Suspiciousness Metrics From Hybrid Data Set for Boosting a
Spectrum Based Fault Localization,” in IEEE Access, vol. 8, pp. 198451-198467, 2020, doi: 10.1109/ACCESS.2020.3035413.
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Kabir Sulaiman Said, Liming Nie, Adekunle Akinjobi Ajibode, and Xueyi Zhou. 2020. GUI testing for mobile applications: objectives, approaches and challenges. In 12th Asia-Pacific Symposium on Internetware (Internetware’20), May 12–14, 2021, Singapore, Singapore. ACM, New York, NY, USA, 10 pages. https://doi.org/10.1145/3457913.3457931
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Ajibode, Adekunle, Ting Shu, Kabir Said, and Zuohua Ding. 2022. “A Fault Localization Method Based on Metrics Combination” Mathematics 10, no. 14: 2425. https://doi.org/10.3390/math10142425
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Ajibode, Adekunle, Ting Shu, Laghari Gulsher, and Zuohua Ding. 2022. “Effectively Combining Risk Evaluation Metrics for Precise Fault Localization” Mathematics 10, no. 21: 3924. https://doi.org/10.3390/math10213924
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Ajibode, Adekunle, Apedo Yvon, Ajibode Temitope. 2024. “Systematic literature review on forecasting and prediction of technical debt evolution”
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Ajibode, Adekunle, Dong Yunwei, Yang Hongji. 2024. “Software issues report for bug fixing process: An empirical study of machine-learning libraries”
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Ajibode, A., Bangash, A. A., Cogo, F. R., Adams, B., & Hassan, A. E. (2024). Towards Semantic Versioning of Open Pre-trained Language Model Releases on Hugging Face.