About

Onyeka Emebo is a Collegiate Assistant Professor in the Department of Computer Science at Virginia Tech, located in Torgersen Hall, Blacksburg, VA. He holds a Ph.D. in computer science from Covenant University, Nigeria, earned in 2017, along with a master's degree obtained in 2009 and a bachelor's degree in 2006, both from the same institution. His research interests include data analytics, information retrieval, machine learning, natural language processing, digital education, software engineering, and related areas. Emebo's academic and professional background is rooted in computer science, with a focus on advancing knowledge and applications within these fields.

Research topics

• Computer Science
• Artificial Intelligence
• Machine Learning
• Data Mining
• Statistics
• Mathematics
• Biology
• Medicine
• Risk analysis (engineering)
• Business
• Knowledge management
• Software engineering

Selected publications

• JASPEX model

  Figshare · 2026-01-01

  datasetOpen accessSenior author

  JASPEX model was developed and extensively and rigorously programmed over many years by [Dr.Olugbenga Oluwagbemi]. This GitHub project data also contains processed weather collection data for the region of study from year 2006 to year 2019. https://github.com/oluwagbemi/Enhanced-Computational-Model-Project-2018-2026

  PublisherDOI

• Acceptability, User Satisfaction Measurement and Comparison of Speech and DTMF for Supermarket-Based Spoken Dialogue System for Shopping

  Lecture notes in networks and systems · 2025-01-01

  book-chapter
  PublisherDOI

• Multilingual voice-enabled informatics tools: Catalyst for equitable AI in HIV and HIV-comorbidity healthcare management

  PLoS ONE · 2025-10-21 · 1 citations

  articleOpen accessCorresponding

  Human Immunodeficiency Virus (henceforth HIV) is a global health problem, presently with no known cure. Africa has one of the highest incidences of HIV. Nigeria, within the West African (WA) region, is one of the largest economies on the continent. However, the country continues to struggle with HIV, with approximately 2 million individuals currently infected and experiencing ongoing transmissions. Management of the disease has been difficult due to communication barriers between English-speaking medical practitioners and indigenous patients in rural and suburban regions of the country and bordering countries. In this paper, we used fuzzy logic and voice-enabled technology to create WAHMIDS (West African HIV and HIV-comorbidity Multilingual Indigenous Diagnostic Software) and WAHMIMA (West African HIV Multilingual Informatics Mobile Application), which are health apps designed to help diagnose HIV and manage related health issues in both rural and urban areas for people who speak different indigenous languages in West Africa. Additionally, illustrations of the application of this tool to HIV diagnosis, using existing HIV data, are demonstrated. We expect that these tools will assist English-speaking medical workers and inhabitants of West African communities in their efforts to control HIV transmissions. These informatics tools have the potential to help prescribe medications for HIV and HIV-comorbidity patients. We anticipate that these informatics tools will help address healthcare disparities and promote diversity, equality, and inclusion by reducing the gaps in healthcare delivery between different regions and facilitating the collection of diverse patient data, which is essential for developing and planning more inclusive and accurate healthcare strategies in the West African sub-region.

  PublisherDOI

• Design and Implementation of a Web-Based Application for Managing Agricultural Health Products

  2024-07-23 · 2 citations

  article

  Caring for the health of food crops and plants can help boost food production and eradicate hunger according to the second United Nations (UN) Sustainable Development Goal (SDG). The procurement of agricultural health products such as fertilizers, fungicides, pesticides, and herbicides are a major problem for an average Nigerian farmer. This results in low crop yield and negatively impacts on food production which eventually causes hunger in the land. Existing methods of procuring these health products have majorly been through offline platforms such as agricultural stores and other relevant stores. This has its disadvantages such as inaccessible roads to stores where such products can be obtained, varying prices, health products out of stock, ignorance in the application of such products. These barriers deter farmers from procuring these health products. In this paper, a survey was conducted on the needs and problems of farmers. The results of the survey informed the design and implementation of an agricultural health Informatics web application for health product management for food crops. The application was designed using unified modelling language class diagram and implemented using Python. SQLite3 serves as the backend database. The agricultural informatics solution will help farmers in Nigeria to easily procure health products for food crops and get the products delivered without stress and worry when fully deployed. This will boost food production, thus eradicating hunger; it will also help in exporting food crops to other countries.

  PublisherDOI

• Facial Emotion Recognition and Classification Using the Convolutional Neural Network-10 (CNN-10)

  Applied Computational Intelligence and Soft Computing · 2023-10-13 · 12 citations

  articleOpen access

  The importance of facial expressions in nonverbal communication is significant because they help better represent the inner emotions of individuals. Emotions can depict the state of health and internal wellbeing of individuals. Facial expression detection has been a hot research topic in the last couple of years. The motivation for applying the convolutional neural network-10 (CNN-10) model for facial expression recognition stems from its ability to detect spatial features, manage translation invariance, understand expressive feature representations, gather global context, and achieve scalability, adaptability, and interoperability with transfer learning methods. This model offers a powerful instrument for reliably detecting and comprehending facial expressions, supporting usage in recognition of emotions, interaction between humans and computers, cognitive computing, and other areas. Earlier studies have developed different deep learning architectures to offer solutions to the challenge of facial expression recognition. Many of these studies have good performance on datasets of images taken under controlled conditions, but they fall short on more difficult datasets with more image diversity and incomplete faces. This paper applied CNN-10 and ViT models for facial emotion classification. The performance of the proposed models was compared with that of VGG19 and INCEPTIONV3. The CNN-10 outperformed the other models on the CK + dataset with a 99.9% accuracy score, FER-2013 with an accuracy of 84.3%, and JAFFE with an accuracy of 95.4%.

  PublisherOA PDFDOI

• Repositioning industry R&D units into tertiary education research laboratories

  International Journal of Business and Globalisation · 2023-01-01

  articleOpen accessSenior author

  Research and development (R&D) play a crucial role in the development and sustainability of many economies. Therefore, world leaders in developed and developing countries have consciously engaged R&D activities to improve their cities, standard of living of its citizenry and installation of adequate military defence systems. Global spending on research and development (R&D) has reached a high of almost US $1.7 trillion dollars in 2017. The study posits that public and private firms can reposition its R&D units into research laboratories in tertiary institutions which can result in mutual benefits for both institutions. The study showed how industry R&D units can be interpolated with existing tertiary education research laboratories by developing a framework for successful integration and migration. In addition, the study showed that there are drivers and barriers in the collaborative framework between Industry and education research labs.

  PublisherOA PDFDOI

• The future of education: a disruptive framework that bridges policies and quality education

  International Journal of Business and Globalisation · 2023-01-01

  article

  The world, as we used to know it, is not on the same level again. Consequently, the level and type of education dished out to students need to be reviewed from time to time. The level of innovation and skill required in industries need to be disruptive to serve the students of the future. The study examined the future of education using disruptive frameworks that bridges policies and quality education. The study utilised an in-depth content analysis of existing literature on the future of education. Using the review, the data was presented using frameworks to depict solutions for bridging policies and the future of quality education. There is need for intentional reviews of institutional policies and technical frameworks in the educational sector that meets the demand of the fast-paced world of work. The study presented headings on what educators need to know, the classroom of the future, gaming as a tool for education and the role of policy makers in the future of education. In conclusion, the Nigerian educational sector needs disruptive frameworks and technologies that guarantee the future of education.

  PublisherDOI

• The future of education: a disruptive framework that bridges policies and quality education

  International Journal of Business and Globalisation · 2023-01-01

  articleSenior author

  The world, as we used to know it, is not on the same level again. Consequently, the level and type of education dished out to students need to be reviewed from time to time. The level of innovation and skill required in industries need to be disruptive to serve the students of the future. The study examined the future of education using disruptive frameworks that bridges policies and quality education. The study utilised an in-depth content analysis of existing literature on the future of education. Using the review, the data was presented using frameworks to depict solutions for bridging policies and the future of quality education. There is need for intentional reviews of institutional policies and technical frameworks in the educational sector that meets the demand of the fast-paced world of work. The study presented headings on what educators need to know, the classroom of the future, gaming as a tool for education and the role of policy makers in the future of education. In conclusion, the Nigerian educational sector needs disruptive frameworks and technologies that guarantee the future of education.

  PublisherDOI

• Repositioning industry R&D units into tertiary education research laboratories

  International Journal of Business and Globalisation · 2023-01-01

  article1st authorCorresponding

  Research and development (R&D) play a crucial role in the development and sustainability of many economies. Therefore, world leaders in developed and developing countries have consciously engaged R&D activities to improve their cities, standard of living of its citizenry and installation of adequate military defence systems. Global spending on research and development (R&D) has reached a high of almost US $1.7 trillion dollars in 2017. The study posits that public and private firms can reposition its R&D units into research laboratories in tertiary institutions which can result in mutual benefits for both institutions. The study showed how industry R&D units can be interpolated with existing tertiary education research laboratories by developing a framework for successful integration and migration. In addition, the study showed that there are drivers and barriers in the collaborative framework between Industry and education research labs.

  PublisherDOI

• Using Deep 1D Convolutional Grated Recurrent Unit Neural Network to Optimize Quantum Molecular Properties and Predict Intramolecular Coupling Constants of Molecules of Potential Health Medications and Other Generic Molecules

  Applied Sciences · 2022-07-18 · 6 citations

  articleOpen access

  A molecule is the smallest particle in a chemical element or compound that possesses the element or compound’s chemical characteristics. There are numerous challenges associated with the development of molecular simulations of fluid characteristics for industrial purposes. Fluid characteristics for industrial purposes find applications in the development of various liquid household products, such as liquid detergents, drinks, beverages, and liquid health medications, amongst others. Predicting the molecular properties of liquid pharmaceuticals or therapies to address health concerns is one of the greatest difficulties in drug development. Computational tools for precise prediction can help speed up and lower the cost of identifying new medications. A one-dimensional deep convolutional gated recurrent neural network (1D-CNN-GRU) was used in this study to offer a novel forecasting model for molecular property prediction of liquids or fluids. The signal data from molecular properties were pre-processed and normalized. A 1D convolutional neural network (1D-CNN) was then built to extract the characteristics of the normalized molecular property of the sequence data. Furthermore, gated recurrent unit (GRU) layers processed the extracted features to extract temporal features. The output features were then passed through several fully-connected layers for final prediction. For both training and validation, we used molecular properties obtained from the Kaggle database. The proposed method achieved a better prediction accuracy, with values of 0.0230, 0.1517, and 0.0693, respectively, in terms of the mean squared error (MSE), root mean square error (RMSE), and mean absolute error (MAE).

  PublisherOA PDFDOI

Frequent coauthors

• Olugbenga Oluwagbemi

  Middlesex University

  11 shared

• Olawande Daramola

  University of Pretoria

  8 shared

• Adedeji Afolabi

  Virginia Tech

  5 shared

• Aparna S. Varde

  Montclair State University

  5 shared

• Patience Tunji Olayeni

  Covenant University

  4 shared

• Emmanuel Gbenga Dada

  4 shared

• David Opeoluwa Oyewola

  4 shared

• Sanjay Misra

  Institute for Energy Technology

  4 shared