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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
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Posts
Future Blog Post
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Blog Post number 4
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Blog Post number 3
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Blog Post number 2
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portfolio
Concept-based Explanation of Deep Visual Categorization Models
CNNs lack human-centred explainability in their natural forms, despite their efficiencies. An ongoing project and a requirement for the completion of a PhD at The School of Engineering and Built Environment, Griffith University, I aim to reveal what a CNN sees and not just where it looked. 
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Intelligent Wear Monitoring of Micro Drill Bit Automatic Regrinding In-Line Systems
This project addresses the challenge of extracting discriminant information from multiple sensors exhibiting unique spectral and transient behaviors—a critical need in modern diagnostic systems. Focusing on high-precision automatic regrinding equipment used for micro drill bits, the study emphasizes real-time monitoring during the grinding process to safeguard drill bit longevity and overall equipment performance. 
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ACADIC: Towards an Inclusive Data Governance Policy for the use of AI in Africa
Honoured to be on a panel discussion at the Data for Policy Conference hosted at the Evans School of Public Policy & Governance, University of Washington on Towards an Inclusive Data Governance Policy for the use of AI in Africa alongside Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC) colleagues (Jude Kong and Jake Okechukwu Effoduh), moderated by the International Development Research Centre (IDRC) project officer Chaitali Sinha.
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Intelligent Condition Monitoring Framework For Solenoid Pumps
Under Prof. Hur Jang-Wook’s supervision, I spearheaded this project between March 2019 and May 2021 as a requirement for fulfilling the requirements of masters (by research) at the Department of Mechanical Engineering (Department of Aeronautics, Mechanical and Electronic Convergence Engineering), Kumoh National Institute of Technology (KIT), Republic of Korea. 
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FMECA and Intelligent Fault Diagnostics of Gear Pumps
Under Prof. Hur Jang-Wook’s supervision, I collaborated with a team member as part of his Masters (by research) requirements at the Department of Mechanical Engineering (Department of Aeronautics, Mechanical and Electronic Convergence Engineering), Kumoh National Institute of Technology (KIT), Republic of Korea. 
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An Investigation For Optimal Water Composition In Emuslified Diesel Fuel Engines
About 30% of greenhouse gas emissions come from diesel engines, which contribute to a variety of health and environmental problems. This project was motivated by the need to discover the optimal diesel emulsion to reduce fuel emmision, maintain engine efficiency and lower costs. 
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Optimum Gasket Material Selection for PEM Fuel Cells Using Finite Element Analysis
The project proposed an informed decision-making framework for remaining compliant with domestic and international standards while also improving performance and extending the life cycles of proton-exchange membrane fuel cells (PEMFC) using Finite Element Analysis (FEA). 
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Fault Diagnosis of Electrical motor
The project aimed at developiing fault disgnostic frameworks for electrical motors. Supervised by Prof. Hur Jang Wook and spearheaded by myself, the team designed test beds, conducted experiments and authored a journal articles. 
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Fault Diagnosis of Electronic Components: Switch-mode AC/DC power supply
The project aimed at developiing fault disgnostic frameworks for electronic (capacitors, etc) components. Supervised by Prof. Hur Jang Wook and spearheaded by myself, the team designed test beds, conducted experiments and authored a journal articles. 
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Smart Factory Automation Modelling: A.I. Dehumidification Control System
About 30% of greenhouse gas emissions come from diesel engines, which contribute to a variety of health and environmental problems. This project was motivated by the need to discover the optimal diesel emulsion to reduce fuel emmision, maintain engine efficiency and lower costs. 
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Rolling Element Bearing Failure Prognostics and RUL Estimation
The project Explores different statistical and machine learning methods for estimating the remaining useful life (RUL) of Rolling Elemnet Bearings. 
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publications
[Best Paper]A Feature Fusion-based Prognostics Approach for Rolling Element Bearings
Published in 5th International Conference on Materials and Reliability Jeju, Korea, 2019
This short paper proposes a kernel principal component analysis (KPCA) feature fusion technique for degradation assessment, and a deep learning model for prognostics of rolling element bearings. Read more
Recommended citation: U. E. Akpudo and J. H. Hur, “A Feature Fusion-based Prognostics Approach for Rolling Element Bearings,” 5th International Conference on Materials and Reliability Jeju, Korea, Nov. 27-29, 2019.
Download Paper | Download Slides
A Cost-Efficient MFCC-Based Fault Detection and Isolation Technology for Electromagnetic Pumps
Published in IEEE Access, 2020
This study presents a robust approach for vibration-based failure diagnostics of electromagnetic/solenoid pumps which employ a multi-domain feature extraction procedure (statistical time-domain and frequency-domain features, Mel frequency cepstral coefficients, and continuous wavelet coefficients) for capturing linear and nonlinear properties from the signals. Read more
Recommended citation: U. E. Akpudo and H. Jang-Wook, "A Multi-Domain Diagnostics Approach for Solenoid Pumps Based on Discriminative Features," in IEEE Access, vol. 8, pp. 175020-175034, 2020, doi: 10.1109/ACCESS.2020.3025909.. Published in Journal of Mechanical Science and Technology (JMST), 2020 This study presents a methodology for constructing a reliable HI for bearing prognostics, choosing a reliable TSP, and provides a comparison between ML and DL methods for bearing prognostics. Read more Recommended citation: Akpudo, U.E., Hur, JW. Towards bearing failure prognostics: a practical comparison between data-driven methods for industrial applications. Journal of Mechanical Science and Technology (JMST) 34, 4161–4172 (2020). https://doi.org/10.1007/s12206-020-0908-7 Published in IEEE Access, 2021 This study introduces a multi-sensor prognostics approach which merges highly prognosible statistical features from vibrational and pressure sensor measurements after a multi-level wavelet decomposition of the signals. Read more Recommended citation: U. E. Akpudo and H. Jang-Wook, "An Automated Sensor Fusion Approach for the RUL Prediction of Electromagnetic Pumps," in IEEE Access, vol. 9, pp. 38920-38933, 2021, doi: 10.1109/ACCESS.2021.3063676. Published in Electronics, 2021 This study proposes the use of common rail (CR) pressure differentials and a deep one-dimensional convolutional neural network (1D-CNN) with the local interpretable model-agnostic explanations (LIME) for empirical diagnostic evaluations (and validations) using a KIA Sorento 2004 four-cylinder line engine as a case study. Read more Recommended citation: Akpudo, U.E.; Hur, J.-W. An Explainable DL-Based Condition Monitoring Framework for Water-Emulsified Diesel CR Systems. Electronics 2021, 10, 2522. https://doi.org/10.3390/electronics10202522. Published in Energies, 2021 This study proposes a hybrid DNN and one-dimensional CNN diagnostics model (D-dCNN) which automatically extracts high-level discriminative features from vibration signals for fault detection and isolation (FDI). Read more Recommended citation: Akpudo, U.E.; Hur, J.-W. D-dCNN: A Novel Hybrid Deep Learning-Based Tool for Vibration-Based Diagnostics. Energies 2021, 14, 5286. https://doi.org/10.3390/en14175286 Published in Algorithms, 2022 This study explores artificial intelligence-based models for learning the discriminant spectral information stored in the vibration signals and considers the accuracy and cost implications of spectral isolation of the critical spectral segments of the signals for accurate equipment monitoring. Read more Recommended citation: Akpudo, U.E.; Hur, J.-W. Exploring the Efficiencies of Spectral Isolation for Intelligent Wear Monitoring of Micro Drill Bit Automatic Regrinding In-Line Systems. Algorithms 2022, 15, 194. https://doi.org/10.3390/a15060194. Published in Data for Policy 2022, 2022 This brief unveils some vulnerabilities surrounding the use of AI in SSA and promotes equitable access to new technologies in SSA amidst the anxiety around AI and concerns about data governance. Read more Recommended citation: J. O. Effoduh, U. E. Akpudo, and J. D. Kong, “Toward a trustworthy and inclusive data governance policy for the use of artificial intelligence in Africa,” Data & Policy, vol. 6, p. e34, 2024. doi:10.1017/dap.2024.26. Published in 2023 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2023 This study explores and draws for the first time, qualitative insights into Ultra-FGVC images through saliency-based explanation methods that provide intuitive hints on where the models are looking at the images. Read more Recommended citation: U. E. Akpudo, X. Yu, J. Zhou and Y. Gao, "What EXACTLY are We Looking at?: Investigating for Discriminance in Ultra-Fine-Grained Visual Categorization Tasks," 2023 International Conference on Digital Image Computing: Techniques and Applications (DICTA), Port Macquarie, Australia, 2023, pp. 129-136, doi: 10.1109/DICTA60407.2023.00026. Published in 2024 IEEE International Conference on Multimedia and Expo (ICME), 2024 This paper extends the Invertible Concept-based Explainer (ICE) to introduce a new ingredient measuring concept consistency. Read more Recommended citation: U. E. Akpudo, Y. Gao, J. Zhou and A. Lewis, "Coherentice: Invertible Concept-Based Explainability Framework for CNNs beyond Fidelity," 2024 IEEE International Conference on Multimedia and Expo (ICME), Niagara Falls, ON, Canada, 2024, pp. 1-6, doi: 10.1109/ICME57554.2024.10687699. Published: I had the opportunity to present my insights on how Big Data-driven Prognostics and Health Management (PHM) is shaping the future of industrial reliability. Read more Published: Addressed AI’s role in early disaster warning systems, climate adaptation strategies, and risk mitigation. Showcased case studies on AI-driven sustainable urban water systems. Read more Published: Discussed how AI can enhance predictive flood monitoring, real-time water quality assessment, and smart irrigation systems. Explored machine learning applications in optimizing hydropower efficiency and water distribution networks. Read more Published: Anchored a one-week workshop organised by Defense Reliability Laboratory, Kumoh National Institute of Technology for graduate and undergraduate students for practical approaches to data-driven prognostics and health management of mechanical, electrical and electronic components. Read more Published: Anchored a one-week workshop organised by Defense Reliability Laboratory, Kumoh National Institute of Technology for graduate and undergraduate students for practical approaches to data-driven prognostics and health management of mechanical, electrical and electronic components. Read more Published: Honoured to pitch my research proposal to Hanwa Systems on Emulsified Diesel Injection Systems Monitoring using intelligent PHM frameworks Read more Published: Pitched my proposal Smart Factory Automation: A correlation-based GA-DNN Model for Smart AC Monitoring and Control at the Daewoong Foundation AI & Big Data Hackathon organised by Daewoong Foundation. Read more Published: This initiative provides a platform for fostering cultural awareness and inclusivity through structured dialogues, exhibitions, presentations, and interactive sessions amongst high and middle school children. Read more Published: Honoured to be on a panel discussion at the Data for Policy Conference on Towards an Inclusive Data Governance Policy for the use of AI in Africa alongside Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC) colleagues (Jude Kong and Jake Okechukwu Effoduh), moderated by the International Development Research Centre (IDRC) project officer Chaitali Sinha (she/her). Read more Published: Pitched my proposal to 3rd Smart Agriculture Symposium organised by the ARC Research Hub for Driving Farming Productivity and Disease Prevention, Griffith University Australia. Read more Published: Pitched my proposal to different talent groups at the Emerging Industry Leaders Program organised by Griffith University Australia. Read more Published: Pitched my proposal on Unveiling AI Concerns for Sub-Saharan Africa and Other Vulnerable Groups’ at the ICONIC 2024 Read more Undergraduate course, University 1, Department, 2014 This is a description of a teaching experience. You can use markdown like any other post. Read more Workshop, University 1, Department, 2015 This is a description of a teaching experience. You can use markdown like any other post. Read more
Download Paper</p> </article> </div> Towards bearing failure prognostics: a practical comparison between data-driven methods for industrial applications
Download Paper</p> </article> </div> An Automated Sensor Fusion Approach for the RUL Prediction of Electromagnetic Pumps
Download Paper</p> </article> </div> An Explainable DL-Based Condition Monitoring Framework for Water-Emulsified Diesel CR Systems
Download Paper</p> </article> </div> D-dCNN: A Novel Hybrid Deep Learning-Based Tool for Vibration-Based Diagnostics
Download Paper</p> </article> </div> Exploring the Efficiencies of Spectral Isolation for Intelligent Wear Monitoring of Micro Drill Bit Automatic Regrinding In-Line Systems
Download Paper</p> </article> </div> Towards an Inclusive Data Governance Policy for the use of AI in Africa
Download Paper | Download Slides What EXACTLY are We Looking at?: Investigating for Discriminance in Ultra-Fine-Grained Visual Categorization Tasks
Download Paper Coherentice: Invertible Concept-Based Explainability Framework for CNNs beyond Fidelity
Download Paper | Download Slidestalks
🎙️Breaking the Walls of Reliability - Fallings Walls Lab Seoul 2019
🎙️AI-Powered Disaster Resilience & Climate Adaptation
🎙️AI-Driven Innovations in Water Security
🎙️Lecture: DRL FSecond Winter Workshop organised by Defense Reliability Laboratory
🎙️Lecture: DRL First Winter Workshop organised by Defense Reliability Laboratory
🎙️Hanwa Systems Pitch: Emulsified Diesel Injection Systems Monitoring
🎙️Pitch: Smart Factory Automation
🎙️Guest Tutor, Global Understanding Educational Program, Kumoh National Institute of Technology, South Korea
🎙️Panel Discussion: Towards an Inclusive Data Governance Policy for the use of AI in Africa
🎙️Presenter, 3rd Smart Agriculture Symposium
🎙️Ideation: Emerging Industry Leaders Program
🎙️Talk at the ICONIC 2024 Conference
teaching
Teaching experience 1
Teaching experience 2