Halleluyah Oluwatobi AWORINDE
college of computing and communication studies (COCCS)
Dr. Halleluyah Oluwatobi AWORINDE holds a teaching position with the College of Computing & Communication Studies, Bowen University, Iwo, Nigeria and as well, a Research Fellow at Computing and Analytics Research Laboratory. Dr. Aworinde is currently the Director of Digital Services at Bowen University and as well, serve on several committees in the university.
- PhD (2020) Ladoke Akintola University of Technology, Ogbomoso (Computer Science)
- MSc (2015) University of Ibadan, Ibadan (Computer Science)
- B.Tech (2010) Ladoke Akintola University of Technology, Ogbomoso (Computer Science)
To date, my research can be broadly summarized into four thrusts: pattern recognition, Deep Learning frameworks for social good, AI-driven smart farming and Mechanism Design-based Security Game Models.
Pattern Recognition. Due to paucity of information on the possibility of ethnicity identification through fingerprint biometric characteristics, my Master’s dissertation developed a soft computing model through the combination of two biometric traits (Gender and Ethnicity) in order to ascertain if individual of different ethnicities and gender can be identified through their fingerprint. Model development was achieved using localized dataset from major ethnic groups in Nigeria and of both gender (male and female) across all ages. KNN was used for classification with prediction accuracy of about 95%. The possibility of identifying a person’s ethnicity and gender through fingerprint patterns was ascertained and confirmed.
Also, a model for car plate recognition and speed tracking was developed using machine learning algorithms. The model consists of recognition modules such as image acquisition, Gaussian blur, localisation of car plate, character segmentation and optical character recognition of car plate. K-NN Algorithm was used for training licensed plate font type spanning A-Z and 0-9 while the speed tracking module used a camera which is automatically self-initiated to track the speed of any moving object within its range of focus. The performance of the model was evaluated using metrics such as recognition accuracy, positive prediction value, negative prediction value, specificity and sensitivity. A tracking accuracy of 82% was achieved.
Another research carried out under this cluster modelled interactions driving breast cancer development. The research was conducted at the 2020 Alan Turing Institute Data Study group and datasets were made available by the Cancer Research UK (CRUK). In the research, RNA sequencing data was studied to reverse engineer the connectivity network between genes in ER+ breast cancer. Twenty (20) different perturbations were performed by knocking down genes that are known to interact with the ER in breast cancer cells. Two classes of genes were distinguished i. e. the target gene and the response gene. We explored different types of network models that can be used to model the dependencies between genes; such include Nested Effect Model (NEM), Convolutional Neural Network (CNN), Graph Neural Networks (GNN) and Bayesian Network (BN). Differentially expressed gene data allowed us to build a very interpretable network that show links between genes.
Deep Learning Frameworks for Social Good. While my Master’s research ascertained the possibility of using soft biometric traits to categorise individual personalities, I took a leap forward for my PhD in applying the findings to real life issues that bother on security. In essence, deep learning frameworks were developed to streamline search range of perpetrator(s) of crime through their ethnic divide. In this case, both supervised (Convolutional Neural Networks – CNN) and unsupervised deep learning (Deep Belief Network – DBN) techniques were explored. Work on Car Crash Predictive Model Using Driver’s Behavioural Pattern: Recurrent Neural Network approach won a Best Poster Award (2nd) at the 2020 Data Science Nigeria AI Bootcamp; work is ongoing on it.
AI-driven smart farming. One of the focal thrusts of my research adventure is proffering AI solutions to drive smart farming with an expectation of having increase in yield. Research on precision farming solution using wireless sensor network to increase agricultural productivity in Nigeria was done. With this, the system has the capacity to sense environmental parameters and thereafter transmits its findings to the base station for farmers to make decisions such as actuating irrigation scheduling, fertilisation scheduling, etc. Other related works in this area of research include Deep Learning based farmland bird detection and dispersal system which was presented as a poster at the 3rd TWAS Young Affiliates Network (TYAN) International Thematic Workshop on Big Data, Analytics and Machine Intelligence. Research to bridge the gap between the current and desired capabilities of agricultural outputs in Nigeria through the development of a sustainable smart farm solution. The objectives are to develop autonomous Unmanned Aerial Vehicle capable of scouting cultivated field while collecting multispectral and hyperspectral data using sensors. A data analytic system will be developed for diseases, pest and yield detection and estimation. The system will be tested and evaluated among a network of small-scale farmers for a period of a farming season.
Mechanism Design-Based Security Game Models. My research work on Learning Attackers’ Behavioural Patterns for Strategic Defense in Nigeria got me an Honourable Mention Award at the 21st ACM Conference on Economics and Computation. The research which is still an ongoing work propose Stackelberg Security Game model for learning the style of attackers especially in an insurgence-ridden country as Nigeria. This research intends to conceptualize a holistic approach to tackling and mitigating insurgency using geospatial model and Mechanism Design-based security game models to learn the behavioural pattern of the attackers to properly put in place, a formidable security apparatus and as a result, secure the territorial boarders. This approach marks a sharp departure from existing models which hitherto yielded little or no success in the past years. Part of this work got me Poster Presentation Prize out of 136 presenters at the 2022 Deep Learning Indaba held at Tunis, Tunisia.
- Director of Digital Services
- Member, Postgraduate College Board
- Member, Senate Committee on NUC Accreditation
- Member, University VC Transition Committee
- Member, University Convocation Planning Committee
- Reviewer, 2023 Deep Learning Indaba Short Papers and Posters
- Reviewer, 2024 Winter Conference on Computer Vision Papers
- Guest Editor, MDPI Special Issue on Big Data Analytics and Health Informatics
- Co-Chair, Digital Communications Committee of AfriCHI 2023 Conference
- Member, Governing Council Committee on ICT Policy, Bowen University, Iwo, Nigeria
- Member, NITDA Volunteer Expert Group for National Artificial Intelligence Policy – National Information Technology Development Agency (NITDA)
- Reviewer, Early Career and Postgraduate Research Grant Application for Data Science Africa
- Member, IT Certification Training Policy Review Committee on Bowen University & New Horizons Systems Solution Joint MoU
- Segun Adebayo, Halleluyah O. Aworinde*, Akinwale O. Akinwunmi, Olufemi M. Alabi, Adebamiji Ayandiji, Aderonke B. Sakpere, Adetoye Adeyemo, Abel K. Oyebamiji, Oke Olaide, Ezenma Kizito (2023). Enhancing Poultry Health Management Through Machine Learning-based Analysis of Vocalization Signals. Data in Brief Elsevier BV, Volume 50, 109528, ISSN: 2352-3409, https://doi.org/10.1016/j.dib.2023.109528
- Halleluyah O. Aworinde, Segun Adebayo, Akinwale O. Akinwunmi, Olufemi M. Alabi, Adebamiji Ayandiji, Aderonke B. Sakpere, Abel K. Oyebamiji, Oke Olaide, Ezenma Kizito, Abayomi J. Olawuyi (2023). Poultry fecal imagery dataset for health status prediction: A case of South-West Nigeria. Data in Brief Elsevier BV, Volume 50, 109517, ISSN: 2352-3409, https://doi.org/10.1016/j.dib.2023.109517
- Akinwale O. Akinwunmi, Halleluyah O. Aworinde, Segun Adebayo, Jacob A. Akinpelu (2023). Geospatial Cloud-Based Model for Mitigating Impact of Natural Disaster and Security Threats Using Smart Digital Devices. International Journal of Wireless and Microwave Technologies (IJWMT). Volume 13, No. 2, pp. 22 -36. https://doi.org/10.5815/ijwmt.2023.02.03
- Segun Adebayo, Halleluyah Oluwatobi Aworinde*, Akinwale O. Akinwunmi, Adebamiji Ayandiji, Awoniran Olalekan Monsir (2023). Convolutional Neural Network-based Crop Disease Detection Model using Transfer Learning Approach. Indonesian Journal of Electrical Engineering and Computer Science Volume 29, No 1, pp. 365 -374. https://doi.org/10.11591/ijeecs.v29.i1.pp365-374
- Aworinde, H.O.*, Afolabi, A.O. & Falohun, A.S. (2020). An Hybridized Dimensionality Reduction Technique in a Generative Deep Learning Domain for Ethnicity Categorization (2020). LAUTECH Journal of Computing and Informatics (LAUJCI). Volume 1, No. 1 pp 99 – 105 ISSN: 2714-4194
- H.O. Aworinde*, A.O. Afolabi, A.S. Falohun and O.T. Adedeji (2019). Performance Evaluation of Feature Extraction Techniques in a Multi-Layer Based Fingerprint Ethnicity Recognition System. Asian Journal of Research in Computer Science 3(1), Pp.1-9. March, 2019, https://doi.org/10.9734/AJRCOS/2019/v3i130084 Published by Science Domain International.
- Aworinde Halleluyah Oluwatobi* and Onifade O.F.W (2019). A Soft Computing Model of Soft Biometric Traits for Gender and Ethnicity Classification. International Journal of Engineering and Manufacturing Vol. 9, No.2 pp.54-63, DOI: 10.5815/ijem.2019.02.05. Published by Modern Education and Computer Science (MECS) https://doi.org/10.5815/ijem.2019.02.05
- Falohun A.S., Aworinde, H.O., Afolabi, A.O. Ismaila, W.O. and Fenwa, O.D. (2018). Fingerprint Phenotyping for Ethnicity Classification: A Generative Deep Learning Perspective. Science Focus (An International Journal of Biological and Physical Sciences) Vol 23(1). https://doi.org/10.36293/sfj.2019.0029
- Akinwale O. Akinwunmi, Halleluyah O. Aworinde and Oliseamaka T. Olise (2015). Design and Implementation of a Model for Information Privacy. International Journal of Applied Information Systems 9(4), Pp.10-16. July 2015. Published by Foundation of Computer Science, New York, USA , https://doi.org.10.5120/ijais15-451388
- S. Adebayo, A.O. Akinwunmi, H.O. Aworinde and E.O. Ogunti (2015). Increasing Agricultural Productivity in Nigeria Using Wireless Sensor Network (WSN). African Journal of Computer & ICTs Vol 8, No.3 Issue 2 Pp 121-128 https://afrjcict.net/wp-content/uploads/2017/08/vol-8-no-3-issue-2-oct-2015ppi-203.pdf
- Aderonke Sakpere, Wonder Osalor, Divine Nwdibuife, Fenton Hughes and Halleluyah Aworinde (2023). A Study on the use of Flipped Classroom in a Mentorship Programme for STEM Females. Conference Proceedings for The 9thInternational Research Symposium on Problem Based Learning 2023 (IRSPBL): Transforming Engineering Education 2023 (TEE 2023) pp 108 – 112 ISBN: 978-87-7573-023-0 ISSN: 2446-3833. Published by Aalborg University Press | forlag.aau.dk
- Akinwale Akinwunmi, Halleluyah Aworinde*, Olalekan Awoniran, Segun Adebayo and Eunice Ogbu (2021). Machine Learning Approach for a cloud-based Smart Farming System. Proceedings of the 4th Biennial Conference on Transition from Observation to Knowledge to Intelligence (TOKI). Pp 55 – 68.
- Aworinde, Halleluyah Oluwatobi*, Salu, John Ayodele, Okedigba, Temilola Oluwafunto & Oladele, Femi (2019). Technological Discourse and Timetable Sytems: Framework Development. Proceedings of the 3rd Biennial International Conference on Transition from Observation to Knowledge to Intelligence (TOKI). Pp.163-180. ISBN: 978-978-976-000-8
- Jaiyeola M.O., Barrett-Baxendale M., Aworinde, H.O. (2015). Performance Evaluation of Big Data Analytics Model for Security Enhancement in Online Payment Systems. Proceedings of the Ninth International Conference on Applications of Information Communication Technologies to Teaching, Research and Administration Vol. IX. Pp. 105-111