Department of Computer Science

Colleges and Faculties > Independent Faculties > Faculty of Science > Department of Computer Science

The Department of Computer Sciences is one of the foundational Departments initially rooted in the Department of Mathematical Sciences, in the Faculty of Science, dedicated to excellence in teaching, research, and community service.

The Department provides rigorous training in various disciplines of Computer Science, including Software Engineering, Data Science, Information Communication Technology, and Cybersecurity, preparing students to contribute meaningfully in applying Computer and Information Communication Technology to provide a foundation and support for modern societal development, sustainability, and scientific advancement.

Vision

“To be a world-class centre of excellence in computer science teaching and research, driving computer technology-enabled innovation and entrepreneurship, advancing secure and sustainable information technologies, and delivering solutions that foster national development and global competitiveness for the betterment of humanity.”

Academic Programmes

The Department offers undergraduate and postgraduate programmes designed to equip students with the theoretical knowledge and practical skills required in Software Engineering, Data Science, Information Communication Technology, and Cybersecurity. Students are exposed to hands-on learning through pragmatic courses, laboratory experiments, and innovative projects that align with global trends in computer sciences.

Research Areas

Research in the Department spans areas such as:

  1. Artificial Intelligence & Machine Learning
  2. Deep learning, reinforcement learning, and natural language processing.
  3. Computer vision and pattern recognition.
  4. Quantum machine learning and AI-inspired optimisation.
  5. Application areas: fraud detection, healthcare analytics, and smart cities.
  6. Cybersecurity & Information Assurance
  7. Network and systems security.
  8. Cryptography and post-quantum security.
  9. Malware analysis, intrusion detection, and zero-day attack prevention.
  10. Digital forensics, cyber threat intelligence, and cyber-physical security.
  11. Data Science & Big Data Analytics
  12. Data mining and predictive analytics.
  13. Scalable algorithms for large datasets.
  14. Cloud-based and distributed data processing.
  15. Applications in business intelligence, finance, and environmental monitoring.
  16. Networking, Cloud & Distributed Systems
  17. Software-defined networking (SDN) and network function virtualization (NFV).
  18. Cloud computing and edge computing.
  19. Internet of Things (IoT) architectures and protocols.
  20. High-performance and parallel computing.
  21. Computational Intelligence & Theoretical Computer Science
  22. Algorithms and complexity theory.
  23. Bio-inspired and evolutionary computing.
  24. Quantum algorithms and computation models.
  25. Graph theory and combinatorial optimization.
  26. Interdisciplinary & Applied Research
  27. Health Informatics – AI for disease prediction and medical image analysis.
  28. Financial Technology (FinTech) – Secure digital banking and fraud prevention.
  29. E-Government & Digital Transformation – Secure tax systems, e-voting, and governance platforms.
  30. Environmental Informatics – Using AI/ML to model groundwater flow, climate change, and renewable energy.

Positioning

The research focus ensures the Department remains at the cutting edge of global computing trends while addressing national development priorities such as cybersecurity, digital transformation, financial inclusion, and sustainable infrastructure.

Facilities for Student Training

The Department is well equipped with modern facilities to support research and teaching:

Physical Infrastructure

  1. Lecture Halls & Classrooms: Smart classrooms with projectors, digital whiteboards, and sound systems, and Flexible seating for collaborative learning.
  2. Computer Laboratories: General-purpose labs for programming, algorithms, and software development
  3. Specialised labs for: Artificial Intelligence & Machine Learning, Cybersecurity & Digital Forensics, Networking & Cloud Computing, Quantum Computing & Simulation (emerging).
  4. Seminar & Workshop Rooms: For guest lectures, hackathons, coding bootcamps, and collaborative research.

Hardware Resources

  1. Student Workstations: High-performance PCs with sufficient RAM (≥16 GB) and GPUs for deep learning.
  2. Servers & Clusters: Central servers for distributed computing and cloud simulations; HPC (High-Performance Computing) cluster for data-intensive research.
  3. Networking Equipment: Routers, switches, and firewalls for hands-on networking and security courses.

Software & Digital Resources

  1. Programming & Development Tools: IDEs (Eclipse, IntelliJ, PyCharm, VS Code, NetBeans).
  2. Specialised Software: MATLAB, Mathematica, RStudio, Qiskit (quantum computing); Network Simulators (NS3, Cisco Packet Tracer, GNS3); Cybersecurity Tools (Wireshark, Kali Linux, Metasploit).
  3. Learning Management Systems (LMS): Moodle, Blackboard, or Canvas for course delivery and assessments.
  4. Digital Libraries & Databases: Access to IEEE, ACM Digital Library, ScienceDirect, SpringerLink.

Teaching & Learning Support

  1. Faculty Offices & Research Labs: For supervision, project guidance, and collaborative work; Peer-assisted coding sessions, debugging clinics, and study groups.
  2. E-learning Infrastructure: High-speed internet and Wi-Fi across campus; Recorded lectures, webinars, and hybrid teaching setups.

Departmental Organogram

Dr Olakunle Olugbenga Solanke

Dr Olakunle Olugbenga SOLANKE is a Reader and researcher in Information Security, with expertise in Network & Systems Security, Cyber Threat Intelligence & Malware Analysis, Artificial Intelligence & Machine Learning for Security, and Quantum Security. He earned his PhD in Computer Science in the year 2017, building on a strong foundation of research in Network Intrusion Detection System (NIDS). He is currently serving as the Acting Head of the Department of Computer Sciences.

His research focuses on Security of Information Systems, with special interest in Intrusion Detection & Prevention Systems (IDPS), Ransomware & Polymorphic Malware – Real-time detection using AI/ML and sandboxing, Adversarial Machine Learning – Studying attacks against ML models, Continual & Online Learning for Malware Detection – Handling evolving threats in real-time, Quantum Machine Learning for Security – Applying quantum algorithms to intrusion and fraud detection, Medical IoT (MIoT) Security – Securing wearable health devices and hospital networks. He has more than forty publications in local and offshore reputable journals and has contributed to advancing knowledge in information systems security through teaching, mentoring, and collaborative research works.

Dr Solanke is passionate about building intelligent, scalable, and impactful solutions for pressing global information security challenges, such as developing prototype platforms for fraud detection, tax management, and malware defence while actively engaged in mentoring and teaching computer communication networks, software engineering, and AI courses.
In his capacity as Acting Head of Department, he oversees academic administration, curriculum development, staff coordination, and student mentoring. He is committed to fostering a culture of academic excellence, collaborative research, and innovation within the Department. His leadership is directed toward strengthening the Department’s visibility and expanding its contributions to solving local and global crop challenges.

Recent Publications

  1. Hassan, S. O., Solanke, O. O., Ajaegbu, C., Odule, T. J., Abdullah, K-K A., Akande, O., and Ayinde, S. (2023). A Triplex Region – Random Early Detection (TR-RED) Algorithm for Active Queue Management in Internet Routers. International Journal of Computing and Digital Systems 14(1):193-201. https://journal.uob.edu.bh:443/handle/123456789/4878 University of Bahrain.
  2. Adesina A. O., Ayo F. E., Ogundele L. A., Solanke O. O., and Abdullah KK. A. (2023). Predicting Cloud Computing Adoption in IoMT Using Deep Learning Approach. Journal of Computer Science and Its Application 30(1):1-9. https://library.ncs.org.ng/download/predicting-cloud-computing-adoption-in-iomt-using-deep-learning-approach/ Nigeria Computer Society.
  3. Hassan S. O., Solanke O. O., Odule T. J., Adesina A. O., Usman S. A., and Ayinde S. A. (2024). AmRED and RED-QE: redesigning random early detection algorithm. Telecommunication Systems. 85(2):263-275. https://doi.org/10.1007/s11235-023-01082-6 Springer.
  4. Hassan S. O., Ajaegbu C., and Solanke O. O. (2024). Double Function Random Early Detection (DFRED): A Revised RED-Oriented Algorithm. Iraqi Journal of Science, 64(10):5241-5252. https://doi.org/10.24996/ijs.2023.64.10.31 University of Baghdad.
  5. Ayo F. E., Awotunde J. B., Ogundele L. A., Solanke O. O., Brahma B., Panigrahi R., and Bhoi A. K. (2024). Ontology-Based Layered Rule-Based Network Intrusion Detection System for Cybercrimes Detection. Knowledge and Information Systems, 66:3355–3392. https://doi.org/10.1007/s10115-024-02068-9 Springer.
  6. Shittu, M. T; Usman, M. A; Solanke, O. O; and Ariyo, S. O. (2024). Investigating the Direction of Groundwater Flow, Drawdown and Over-Pumping in a Confined Aquifer. Journal of Applied Sciences and Environmental Management 28(8):2305-2318. https://www.ajol.info/index.php/jasem/article/view/275495 World Bank assisted National Agricultural Research Programs (NARP), University Of Port Harcourt.
  7. Okesola J. O., Olaniyi I., Ajagbe S. A., Okesola O., Abiodun A. O., Osang F. B., and Solanke O. O. (2024). Predictive analytics on crop yield using supervised learning techniques. Indonesian Journal of Electrical Engineering and Computer Science 36(3):1653~1662.http://doi.org/10.11591/ijeecs.v36.i3 .
  8. Abdullah, K-K. A., Sodimu, S. M., Odule, T. J., Hassan, S. O., Efuwape, B. T., Olasupo, A. O., Solanke, O. O. (2024). Enhance Bert With Radial Basis Function And Multi–Head Attention For Multi–Label Movie Genre Classification: A Transfer Learning Approach. Annals of Faculty Engineering Hunedoara – International Journal of Engineering Tome XXII Fascicule 4, pp.121-126. https://annals.fih.upt.ro/pdf-full/2024/ANNALS-2024-4-15.pdf
  9. Solanke O. O., Hassan S. O., Adamu-Fika F., Mabude C. N., Alaba O. B., and Enem T. A. (2025). Reformed Dropping Function-Based Active Queue Management Mechanism for Network Routers. The Journal of Computer Science and Its Applications. An International Journal of the Nigeria Computer Society (NCS). 31(2):19-31. https://library.ncs.org.ng/download/a-reformed-dropping-function-based-active-queue-management-mechanism-for-network-routers/
  10. Solanke O. O., Abdullah K-K. A., Hassan S. O., Usman M. A., and Adesina A. O (2025). Tax Compliance and Anti-Fraud System for the Nigerian Public Sector. FUW Trends in Science & Technology Journal, 10(1): 327 – 334. e-ISSN: 24085162; p-ISSN: 20485170; https://www.ftstjournal.com/ uploads/docs/ 101Article%2050%20pp%20327-334.pdf
  11. Solanke O. O., Azeez O. M., Abdullah K-K. A., Hassan S. O., Ayo F. E., and Usman M. A. (2025) Sentiment Analysis of Movie Reviews using a Stack-Based Ensemble Method. FUW Trends in Science & Technology Journal, 10(1):270 – 277. e-ISSN: 24085162; p-ISSN: 20485170; April, 2025. https://www.ftstjournal.com/uploads/docs/ 101Article%2042%20pp%20270-277.pdf
  12. Solanke O. O., Abdullah K-K. A., Hassan S. O., and Usman M. A (2025). Enhancing mpMRI-Based Prostate Cancer Detection by Ensemble Quantum Machine Learning Models. Nigerian Journal of Physics (NJP) 34(2):90-98 ISSN online: 3027-0936ISSN print: 1595-0611. https://njp.nipngr.org/index.php/njp/article/view/404/269 June 2025.

Academic Staff

Prof. Ademola Olusola Adesina – Professor of Computer Science, Information Systems, E-health Systems, ICT Applications, Computer Security,
ademola.adesina@oouagoiwoye.edu.ng Orcid ID: 0000-0002-7010-5540; Google Scholar Citations: 602 h-index: 12 i10-index 13 (+234 8035359488) Office Rm. 011
Dr. Olakunle Olugbenga Solanke – Reader (Networking, Information Security, Artificial Intelligence & Machine Learning) solanke.olakunle@oouagoiwoye.edu.ng Orcid ID: 0000-0002-4886-7661; Google Scholar Citations: 46; h-index: 3; i10-index: 1 (+234 8033572759) Office Rm. 008.
Dr. Tola J. Odule – Reader (Cryptography, Information Security, Algorithms) tola.odule@oouagoiwoye.edu.ng Orcid ID: 0000-0002-8400-3000; Google Scholar Citations: 62; h-index: 5; i10-index: 1 (+234 8034274973) Office Rm. 009
Dr. Sakinat Oluwabukonla Folorunso – Reader (Artificial Intelligence, Machine Learning, NLP, Information Retrieval) sakinat.folorunso@oouagoiwoye.edu.ng Orcid ID: 0000-0002-7058-8618; Google Scholar Citations: 1784; h-index: 22; i10-index: 37 (+234 8055369482) Office Rm. 002.
Dr. Khadijat-Kuburat Adebisi Abdullah – Senior Lecturer (Artificial Intelligence, NLP, Semantic Indexing) abdullah.adebisi@oouagoiwoye.edu.ng Orcid ID: 0000-0001-6185-7911; Google Scholar Citations: 23; h-index: 2; i10-index: 0 (+234 8060046592) Office Rm. 009
Dr. Samuel Oluwatosin Hassan – Lecturer I (computer networks and communications, Computational Mathematics) samuel.hassan@oouagoiwoye.edu.ng Orcid ID: 0000-0001-9993-7693; Google Scholar Citations: 84; h-index: 5; i10-index: 3 (+234 7031920552) Office Rm. 005
Dr. Femi Emmanuel Ayo – Lecturer II (Artificial Intelligence, Information Systems, Information Security, Expert Systems) ayo.femi@oouagoiwoye.edu.ng Orcid ID: 0000-0001-8889-5985; Google Scholar Citations: 1089; h-index: 18; i10-index: 27 (+234 8160679722) Office Rm. 019
Dr. Lukman Adebayo Ogundele – Lecturer II (Artificial Intelligence, Information Technology, Cyber Security, Intelligent Systems) ogundele.lukman@oouagoiwoye.edu.ng Orcid ID: 0000-0001-7547-5447; Google Scholar Citations: 82; h-index: 4; i10-index: 3 (+234 8062312269) Office Rm. 019

Non-Academic Staff

Mrs. Ramota Ajoke Osibote – Senior Secretariat Assistant +234 8052332516 Office Rm. 001
Mrs. Motunrayo Yetunde Akinola – Higher Clerical Officer +234 8073089764 Office Rm. 001

Technological Staff

Mrs. Bolajoko Olufunke Adenuga – Assistant Technologist +234 8034991878 

Contact Information

Department Courses

Undergraduate
  1. B.Sc. Computer Science
  2. B.Sc. Cybersecurity
  3. B.Sc. Data Science
  4. B.Sc. Software Engineering
  5. B.Sc. Information and Communication Technology

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2026

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