TITLE (PROF/DR/): DR.

NAME: DOYINSOLA TAOFEKAT AFOLABI

POSITION: LECTURER II

SPECIALISATION:

EDUCATION/TRAINING (Begin with Bachelor’s degree or other initial professional education, such as nursing, include postdoctoral training and residency training if applicable.)

Personal Statement 

I am an early-career researcher and a Computer Sciensist, I am deeply passionate about leveraging Artificial Intelligence to drive impactful, inclusive development. My research explores AI applications in health, education, and environmental sustainability, with a focus on marginalized groups—youths, adolescent girls, and women. I am committed to advancing ethical, context-aware AI solutions that address real-world challenges and promote equity. Through interdisciplinary collaboration and community-centered innovation, I aim to contribute to AI that not only advances technology but also transforms lives. I seek opportunities to further this mission through research, partnerships, and engagement at the intersection of AI and global development.

Positions, Scientific Appointments, and Honours

• Reviewer, International Conference on Information Systems.
• Member, Organizing Committee Conference on Transition from Observation to Knowledge to Intelligence (TOKI, Nigeria, 2019)
• Member, Machine Intelligence Research Group, University of Lagos
• Journal Reviewer (Elsevier-Expert Systems and its Applications)

Selected Most Recent Publications/Contributions to Knowledge

1. Doyin Afolabi, Adewole Philip, Daudu Victor, Sennaike Oladipupo.(2024). ‘COMPARATIVE ANALYSIS OF THE EFFECTIVENESS OF SAMPLING APPROACHES FOR DECISION TREE CLASSIFIER. International Journal of Computer Science and Applications (JCSA) Volume 30, Number 2, December
2. Doyin Afolabi, Oladipupo Sennaike, Shawn Ogunseye, Phillip Adewole (2023) ‘RAMEN: A Ratio-Weighted Majority Entropy-Based Decision Tree Algorithm for Classifying Imbalanced Datasets’, 2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME).
3. Ogunseye, Shawn, Parsons Jeffrey and Afolabi, Doyinsola. (2021). Training-Induced Class Imbalance in Crowdsourced Data. VLDB 2021 Crowd Science Workshop: Trust, Ethics, and Excellence in Crowdsourced Data Management at Scale. 47th International Conference on Very Large Data Bases, Copenhagen, Denmark.
4. Afolabi, D. ,Bamgbade, B. (2021) ‘Near-Optimal Parameter Setting for Decision Tree Data Mining Algorithm’, 1st (Virtual) International Conference on Artificial Intelligence and Robotics (ICAIR), University of Lagos.

Collaborators/ Networks(International inclusive)

1. Olufemi Ogunseye, Bentely University, USA.
2. Eric Hitimana, University of Rwanda, Rwanda