About

Oluwarotimi Williams Samuel, PhD, is a seasoned Computer Scientist and an enthusiastic educator currently serving as a Senior Lecturer in the School of Computing and Engineering at the University of Derby, United Kingdom. Prior to joining the University of Derby, Dr Samuel was an Associate Professor with the Shenzhen Institute of Advanced Technology, Chinese Academy of Science (CAS) and the Shenzhen University of Technology, CAS, where he did his Postdoctoral research fellowship earlier on courtesy of the CAS President's International Fellowship Initiative. Dr. Samuel has led various research projects funded by International, National, Provincial, and Institutional funding agencies, and his scholarly contributions attracted several prestigious academic awards. Additionally, Dr. Samuel worked as an Associate Professor (Adjunct Lecturer) at Dongguan University of Technology and assumed different Information Technology (IT)-inclined roles in various organizations/companies that focused on providing IT services and education. Besides, he is a Visiting Research Fellow at SIAT-CAS and a Research Fellow at INTI International University.

Dr. Samuel's academic journey began with a bachelor’s degree in Computer Science (with First Class Honours) from Kogi State University, followed by a master's degree in Computer Science (with Distinction) from the Federal University of Technology, Akure, both in Nigeria. Afterwards, he obtained a PhD degree in Pattern Recognition and Intelligent Systems from the University of Chinese Academy of Sciences, Beijing, courtesy of the CAS-TWAS President's Fellowship, with excellent dissertation honour and graduate awards.

Dr. Samuel leads and conducts cutting-edge scientific research investigating factors limiting Cyber-physical Systems' practical deployment (including Rehabilitation/Assistive Technologies, Clinical Decision Support Systems, Human-computer Interaction Systems, etc.) and develops novel AI-based data-driven solutions to resolve such limitations. Besides, Dr. Samuel’s scholarly works have yielded several contributions, including 100+ articles in reputable peer-reviewed international journals indexed by the Web of Science (WOS) and IEEE conference proceedings (with 3300+ citations, h-Index: 30, and i10-index: 65 on Google Scholar); “Top Cited/Influential Papers” courtesy of WOS, ESI-Index, and IOP Science; and listed among “Top 2% Scientists Globally” courtesy of Stanford University, USA. In addition, he has received several academic awards and honours, including “IEEE Best Paper Awards”; “IEEE Outstanding Young Investigator Research Visit Award”; “Merit Award for Outstanding Execution of Youth Innovation Project”, “Outstanding Teacher Award”; “Nomination for STEM for Britain Award” that got his work presented in the House of Commons before the British Members of Parliament (MPs); and “several international collaborative research projects” etc.

His unwavering commitment to promoting scientific research, technological innovation, fostering collaboration, and leadership led him to be elected as Chair, Co-chair, and Technical Program Committee Member of various IEEE international conferences and academic meetings. Additionally, this spurred his appointment as an Associate Editor of Frontiers in Big Data Journal, Advisory Board Member of the ELSP International Open Science Platform, and a Distinguished/Invited Speaker by the United Nations (UN) at the Workshop on STI4SDGs Roadmaps and Actions in Africa as well as the Second Forum of the Alliance of Entrepreneurial Universities in Africa.

With a distinguished track record of research, teaching, and services, Dr. Samuel is an exemplary leader in his field, poised to continue making long-lasting contributions to Computing and Applications for sustainable development across sectors for years to come.

Teaching responsibilities

My teaching responsibilities include the following courses:

• Processing Big Data
• Information Visualisation
• Website Technologies
• Data Mining and Foundations of AI
• Multimedia Security

In my previous roles, I have undertaken modules that include:

• Data Science
• Pattern Recognition
• Systems Analysis and Design
• Introduction Programming
• Database Management
• Website Design & Development

In addition to the above modules, I could teach courses on Machine Learning, Data Analytics, AI and Applications, and other Computing-related modules.

Research interests

My research interests revolve around uncovering hidden patterns in structured and unstructured data toward developing simple yet efficient data-driven solutions to resolve real-life problems in the space of Cyber-physical Systems (Assistive Technologies, Clinical Decision Support Systems, Human-computer Interaction Systems, etc.). Thus, I have successfully led my team in conducting cutting-edge fundamental, applied, and interdisciplinary scientific research that resulted in the development of varied novel AI-based data-driven solutions that serve as core drivers for various applications in the areas mentioned above and related fields.

Membership of professional bodies

• Senior Member, The Institute of Electrical and Electronics Engineers (IEEE)
• Member, Biomedical Engineering Association (BMEA)
• Senior Member, IEEE Systems, Man, & Cybernetics Society (SMC)
• Senior Member, IEEE Engineering in Medicine and Biology Society (IEEE-EMBS)
• Member, Association for Computing Machinery (ACM)                  
• Member, Nigerian Institute of Management (NIM)

Qualifications

• Data Science and Machine Learning for Intelligent Data-Driven Solutions, Massachusetts Institute of Technology (MIT), Cambridge, USA (2022)
• Researcher Management & Leadership for Optimisation of Teams, Project, Funding, etc. - University of Colorado, Denver, USA (2022)
• PhD Pattern Recognition and Intelligent Systems (Excellent Dissertation and Graduate Awards) - University of Chinese Academy of Science, Beijing, China (2017)
• Tech Computer Science (Distinction) -Federal University of Technology, Akure, Nigeria (2014)
• BSc Computer Science (First Class Honours) - Kogi State University, Anyigba, Nigeria (2008)
• Oracle Database Administrator Certified Associate (OCA) and Oracle Database SQL Certified Expert (ODBSQLCE) - Oracle University, California, USA (2013)
• Proficiency in Management (PIM)-Nigerian Institute of Management, Lagos, Nigeria (2010)

Recent conferences

• Samuel, O. W.*, Asogbon, M.G., Kulwa F., Zangene A.R., Oyemakinde T.T., Igbe T., McEwan A.A., Li Y., and Li G. (2023). Enhanced Deep Transfer Learning Model based on Spatial-Temporal driven Scalograms for Precise Decoding of Motor Intent in Stroke Survivors. In 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 24^th - 27^th July, 2023, Sydney, Australia
• Zangene, A.R. Samuel O.W.*, Abbasi, A., Nazarpour, K., Li, G. (2023). An Attention-based Bidirectional LSTM Model for Continuous Cross-subject Estimation of Knee Joint Angle during Running from sEMG Signals. 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 24^th - 27^th July, 2023, Sydney, Australia
• Asogbon, M.G., Huai,Y., Samuel, O.W., Jing, Z., Ma, Y., Liu, J., Jiang, Y. Fu, Y., Li, G., and Li, L. (2023). Analysis of Artifactual Components Rejection Threshold towards Enhanced Characterization of Neural Activity in Post-Stroke Survivor. 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 24^th - 27^th July, 2023, Sydney, Australia
• Kulwa, F., Samuel, O.W.*, Asogbon, M. G., Oyemakinde, T. T., Obe, O. O., & Li, G. (2023). A Novel Duo-Stage driven Deep Neural Network Approach for Mitigating Electrode Shift Impact on Myoelectric Pattern Recognition Systems. In 2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA)(pp. 1-6). IEEE, Jeju-Island, South Korea
• Igbe, T., Samuel, O.W., Li, J., Kulwa, F., Kandwal, A., & Nie, Z. (2023). Inspection of EEG Signals for Noninvasive Blood Glucose Monitoring in Prediabetes Diagnosis. In 2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA)(pp. 1-5). IEEE, Jeju-Island, South Korea
• Samuel, O. W., Asogbon, M. G., Esugbe E. Geng, Y., Alberto L.D., Yazan A.J., ... Li, G. (2021). A Low-rank Spatiotemporal based EEG Multi-Artifacts Cancellation Method for Enhanced ConvNet-DL’s Motor Imagery Characterization. In 43nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). October 31^st – November 4^th, 2021
• Asogbon, M. G., Samuel, O. W., Esugbe E. Yazan A.J., ... Li, G. (2021). "HD-sEMG Signal Denoising Method for Improved Classification Performance in Transhumeral Amputees Prosthesis Control. In 43nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). October 31^st – November 4^th, 2021
• Samuel, O. W., Asogbon, M. G., Geng, Y., Rusydi, M. I., Mzurikwao, Z. B., Chen, S., ... & Li, G. (2020). Characterizing Multiple Patterns of Motor Intent Using Spatial-Temporal Information for Intuitively Active Motor Training in Stroke Survivors. In 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)(pp. 3831-3834). IEEE
• Samuel, O. W., Asogbon, M. G., Geng, Y., Li, X., Pirbhulal, S., Chen, S., ... & Li, G. (2019, July). Spatio-temporal based descriptor for limb movement-intent characterization in EMG-Pattern recognition system. In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)(pp. 2637-2640). IEEE
• Samuel, O. W., Asogbon, M. G., Geng, Y., Pirbhulal, S., Mzurikwao, D., Chen, S., ... & Li, G. (2018, October). Determining the Optimal Window Parameters for Accurate and Reliable Decoding of Multiple Classes of Upper Limb Motor Imagery Tasks. In 2018 IEEE International Conference on Cyborg and Bionic Systems (CBS)(pp. 422-425). IEEE
• Samuel, O. W., Asogbon, M. G., Geng, Y., Chen, S., Feng, P., Chuang, L., ... & Li, G. (2018, July). A novel time-domain descriptor for improved prediction of upper limb movement intent in EMG-PR system. In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)(pp. 3513-3516). IEEE
• Samuel, O. W., Li, X., Geng, Y., Feng, P., Chen, S., & Li, G. (2017, July). Motor imagery classification of upper limb movements based on spectral domain features of EEG patterns. In 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)(pp. 2976-2979). IEEE
• Samuel, O. W., Li, X., Fang, P., & Li, G. (2016, July). Examining the effect of subjects' mobility on upper-limb motion identification based on EMG-pattern recognition. In 2016 Asia-Pacific Conference on Intelligent Robot Systems (ACIRS)(pp. 137-141). IEEE
• Samuel, O. W., Li, X., Zhang, X., Wang, H., & Li, G. (2015, October). A hybrid non-invasive method for the classification of amputee’s hand and wrist movements. In International Conference on Biomedical and Health Informatics(pp. 161-166). Springer, Singapore
• Samuel, O. W., & Omisore, M. O. (2013). Hybrid intelligent system for the diagnosis of typhoid fever. J Comput Eng Inf Technol 2: 2. doi: http://dx. doi. org/10.4172/2324, 9307, 2
• Jarrah, Y. A., Grace, A. M., Samuel, O. W.*, Zhu, M., Wang, X., Delis, A. L., ... & Li, G. (2021, March). Enhancement of Upper Limb Movement Classification based on Wiener Filtering Technique. In 2020 IEEE International Conference on E-health Networking, Application & Services (HEALTHCOM)(pp. 1-6). IEEE
• Nsugbe, E., Samuel, O. W.*, Asogbon, M. G., & Li, G. (2020). A Self-Learning and Adaptive Control Scheme for Phantom Prosthesis Control Using Combined Neuromuscular and Brain-Wave Bio-Signals. In Engineering Proceedings, Multidisciplinary Digital Publishing Institute. (Vol. 2, No. 1, p. 59)
• Nsugbe, E., Samuel, O. W., Asogbon, M. G., & Li, G. (2021). Phantom motion intent decoding for transhumeral prosthesis control with fused neuromuscular and brain wave signals. IET Cyber‐Systems and Robotics, 3(1), 77-88
• Asogbon, M. G., Samuel, O. W., Li, X., Jiang, N., Idowu, O. P., Jiang, Y., ... & Li, G. (2020, October). A Robust Multi-Channel EEG Signals Preprocessing Method for Enhanced Upper Extremity Motor Imagery Decoding. In 2020 IEEE International Conference on Mechatronics and Automation (ICMA)(pp. 1929-1934). IEEE
• Deng, H., Cheung, V. C., Geng, Y., Samuel, M. G. A., Samuel, O. W., & Li, G. (2020, July). Robustness of Muscle Synergies under Variant Muscle Contraction Force during Forearm Movements. In 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)(pp. 3306-3309). IEEE
• Idowu, O. P., Samuel, O. W., Li, X., Asogbon, M. G., Fang, P., & Li, G. (2020, June). Efficient classification of motor imagery using particle swarm optimization-based neural network for IoT applications. In 2020 IEEE International Workshop on Metrology for Industry 4.0 & IoT(pp. 600-604). IEEE
• Wang, X., Zhu, M., Wang, X., Liu, S., Samuel, O. W., Yang, W., ... & Li, G. (2020, June). A Pilot Study on Auditory Brainstem Response Evoked with Randomized Stimulation Rate. In 2020 IEEE International Workshop on Metrology for Industry 4.0 & IoT(pp. 349-353). IEEE
• Wang, Y., Yuan, S., Huang, P., Wang, H., Yu, W., Fu, M., Samuel, O.W., ... & Li, G. (2020, June). A New Approach for Hand Gesture Recognition Based on the Fusion of sEMG and Impedance Information. In 2020 IEEE International Workshop on Metrology for Industry 4.0 & IoT(pp. 586-590). IEEE
• Zhu, M., Wang, X., Wang, X., Wang, C., Yang, Z., Samuel, O. W., ... & Li, G. (2020, June). The Effects of Electrode Locations on Silent Speech Recognition using High-Density sEMG. In 2020 IEEE International Workshop on Metrology for Industry 4.0 & IoT(pp. 345-348). IEEE
• Asogbon, M. G., Samuel, O. W., Chen, S., Feng, P., & Li, G. (2019, December). A Hybrid Approach Based on Non-parametric Attribute Learning Technique and Multi-layer Networks for Congestive Heart Failure Risk Prediction. In 2019 IEEE 5th International Conference on Computer and Communications (ICCC)(pp. 257-261). IEEE
• Wang, X., Liu, S., Zhu, M., Wang, X., Liu, Z., Jiang, Y., ... & Li, G. (2019, August). Performance of Flexible Non-contact Electrodes in Bioelectrical Signal Measurements. In 2019 IEEE International Conference on Real-time Computing and Robotics (RCAR)(pp. 175-179). IEEE

In the media

• Exclusive interview with The World Academy of Sciences (TWAS) and publication of an article crafted from the interview. The URL is given as:

https://twas.org/article/can-you-raise-your-arm-now?fbclid=IwAR1Q-8-7D4l4Y6eQuZtcfKE8HymMixGGDQwQ7HWSaC2nO0AOadQg0PCDMrM 

• Exclusive interview with Science and Technology Daily and publication of an article crafted from the interview. The URL is given as:

http://digitalpaper.stdaily.com/http_www.kjrb.com/ywtk/html/2023-04/20/content_552248.htm?div=-1&fbclid=IwAR2WIuKcvNvwbg-0io8QY6X9xwo8JENh5joXJ_POwY1NKVr_Ygb3TCSqZW4

Recent publications

• Wei, W., Tan, F., Zhang, H., Mao, H., Fu, M., Samuel, O. W.*, & Li, G. (2023). Surface electromyogram, kinematic, and kinetic dataset of lower limb walking for movement intent recognition. Scientific Data, Nature, 10(1), 358
• Zangene, A.R., Samuel, O.W.*, Abbasi, A., McEwan, A. A., Asogbon, M.G., Li, G., & Nazarpour, K. (2023). An efficient attention-driven deep neural network approach for continuous estimation of knee joint kinematics via sEMG signals during running. Biomedical Signal Processing and Control, Elsevier, 86, 105103
• Li, H., Han, F., Wang, L., Huang, L., Samuel, O. W., Zhao, H., ... & Liu, Z. (2023). A Hybrid Strategy‐Based Ultra‐Narrow Stretchable Microelectrodes with Cell‐Level Resolution. Advanced Functional Materials, 2300859
• Asogbon M.G., Samuel O.W.*, Ensugbe , et al. (2023). Ascertaining the optimal myoelectric signal recording duration for pattern recognition based prostheses control. Frontiers in Neuroscience, 17
• Ahmad, I., Wang, X., Javeed, D., Kumar, P., Samuel, O.W.*, & Chen, S. (2023). A Hybrid Deep Learning Approach for Epileptic Seizure Detection in EEG signals. IEEE Journal of Biomedical and Health Informatics, April 10
• Samuel O.W.*, Asogbon, M.G., Khushaba, R.N., Kulwa, F., Li, G. (2022). Multiresolution Dual-Polynomial Decomposition Approach for Optimized Characterization of Motor Intent in Myoelectric Control Systems. IEEE Trans. on Biomedical Engineering, Nov. 09, 2022
• Samuel, O.W.*, Asogbon, M.G., Geng, Y., Jiang, N., Mzurikwao, D., Zheng, Y., ... & Li, G. (2021). Decoding movement intent patterns based on spatiotemporal and adaptive filtering method towards active motor training in stroke rehabilitation systems. Neural Computing and Applications, 33(10), 4793-4806
• Jarrah, Y. A., Asogbon, M. G., Samuel, O.W. ^* et al. (2022). High-density surface EMG signal quality enhancement via optimized filtering technique for amputees’ motion intent characterization towards intuitive prostheses control. Biomedical Signal Processing and Control, 74, 103497
• Khushaba, R.N., Al-Timemy, A.H., Samuel, O.W., & Scheme, E.J. (2022). Myoelectric Control With Fixed Convolution-Based Time-Domain Feature Extraction: Exploring the Spatio–Temporal Interaction. IEEE Trans. on Human-Machine Systems. 52(6), 1247-1257
• Samuel, O.W., Yang, B., Geng, Y., Asogbon, M. G., Pirbhulal, S., Mzurikwao, D.,... & Li, G. (2020). A new technique for the prediction of heart failure risk driven by hierarchical neighborhood component-based learning and adaptive multi-layer networks. Future Generation Computer Systems, 110, 781-794
• Samuel, O.W., Asogbon, M. G., Geng, Y., Al-Timemy, A. H., Pirbhulal, S., Ji, N., ... & Li, G. (2019). Intelligent EMG pattern recognition control method for upper-limb multifunctional prostheses: advances, current challenges, and future prospects. IEEE Access, 7, 10150-10165
• Asogbon, M. G., Samuel, O.W. ^#, Geng, Y., Oluwagbemi, O., Ning, J., Chen, S., ... & Li, G. (2020). Towards resolving the co-existing impacts of multiple dynamic factors on the performance of EMG-pattern recognition based prostheses. Computer methods and Programs in Biomedicine, 184, 105278
• Samuel, O.W., Zhou, H., Li, X., Wang, H., Zhang, H., Sangaiah, A. K., & Li, G. (2018). Pattern recognition of electromyography signals based on novel time domain features for amputees' limb motion classification. Computers & Electrical Engineering, 67, 646-655
• Samuel, O.W., Li, X., Geng, Y., Asogbon, M. G., Fang, P., Huang, Z., & Li, G. (2017). Resolving the adverse impact of mobility on myoelectric pattern recognition in upper-limb multifunctional prostheses. Computers in Biology and Medicine, 90, 76-87
• Samuel, O.W., Asogbon, G. M., Sangaiah, A. K., Fang, P., & Li, G. (2017). An integrated decision support system based on ANN and Fuzzy_AHP for heart failure risk prediction. Expert Systems with Applications, 68, 163-172
• Li, X., Samuel, O.W. ^#, Zhang, X., Wang, H., Fang, P., & Li, G. (2017). A motion-classification strategy based on sEMG-EEG signal combination for upper-limb amputees. Journal of Neuroengineering and Rehabilitation, 14(1), 1-13
• Samuel, O.W., Omisore, M. O., & Atajeromavwo, E. J. (2014). Online fuzzy based decision support system for human resource performance appraisal. Measurement, 55, 452-461
• Samuel, O.W., Omisore, M. O., & Ojokoh, B. A. (2013). A web based decision support system driven by fuzzy logic for the diagnosis of typhoid fever. Expert Systems With Applications, 40(10), 4164-4171