Designation
Tutorial Fellow and Timetabling Coordinator- Networks & Applied Computing
Staff E-mail Address
rgikera@kcau.ac.ke
Academic Qualification
- PhD Computer Science – Kenyatta University
- Msc. Computational Neuroimaging (Ongoing) – Univeristy of Edinburgh
- Msc. Computing – Strathmore University
- BEd (Mathematics & Computer Science) – Kenyatta University
- Higher Diploma IT (IMIS) – KCA University
- Diploma IT (IMIS) – Strathmore University
Profile
Dr. Rufus Gikera is deeply passionate about teaching and mentoring the next generation of computer scientists. As a lecturer in Data Science and Machine learning, he actively engages with students, fostering an environment where critical thinking, problem-solving, and creativity flourish. He is committed to nurturing young minds in Computer Science, empowering them to excel, and inspire them to make impactful contributions to both academia and industry. His special research interests are in Computational Neuroimaging, Neurogenomics and Neuroproteomics, with a special focus on modelling brain diseases using Markov Chain Monte Carlo. His broader research interests also span Neuroinformatics and Computational Medicine in general including sub-fields such as Computational Genomics, Computational Molecular Medicine, Computational Anatomy, Computational Physiological Medicine, and Computational Healthcare. With a PhD in Computer Science from Kenyatta University, and currently pursuing an MSc in Computational Neuroimaging at the University of Edinburgh’s College of Medicine, Dr. Rufus Gikera is inspired by the need to bridge the gap between Machine Learning and clinical applications, and help to advance the AI diagnostic techniques and the exciting promise that it holds for improving countless lives.
Selected Publications: Books, Refereed publications & Non Refereed publications
- Optimized K-Means Clustering Algorithm using an Intelligent Stable-plastic Variational Autoencoder with Self-intrinsic Cluster Validation Mechanism. In Proceedings of the 2nd International Conference on Intelligent and Innovative Computing Applications (pp. 1-11). ICONIC. Plaine Magnien, Mauritius. Available in the ACM Digital Library. doi.org/10.1145/3415088.3415125
- K-hyperparameter Tuning in High-dimensional Genomics using Joint Optimization of Deep Differential Evolutionary Algorithm and Unsupervised Learning from Intelligent GenoUMAP Embeddings. International Journal of Information Technology, Springer Nature. https://DOI: 10.1007/s41870-024-02279-x
- K-hyperparameter tuning in High-dimensional Space Clustering: Solving Smooth Elbow Challenges using an Ensemble Based Technique of a Self-adapting Autoencoder and Internal Validation Indexes. Journal of Artificial Intelligence. https://doi.org/10.32604/jai.2023.043229
- Computational Anatomy: K-hyperparameter Tuning of Heart Beat Phonocardiograms using an Improved Autoencoder Pre-trained on Multi-core tSNE. Artificial Intelligence in Medicine, Elsevier. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4820716
- Trends and Advances on the K-Hyperparameter Tuning Techniques in High-Dimensional Space clustering. Indonesian Journal of Artificial Intelligence and Data Mining, 6(2). https://ejournal.uin-suska.ac.id/index.php/IJAIDM/article/view/22718
- Computational Neuroimaging: A systematic Review of Brain MRI Segmentation using K-Means clustering. Clinical Imaging, Elsevier.
- Computational Neuroimaging: Joint Optimization of Deep Multimodal MRI Feature Fusion and Monte-Carol Drop out for Robust Segmentation of Non-Ellipsoidal Brain Tumours. Artificial Intelligence in Medicine, Elsevier.
- Computational Neuroimaging: Deep Ensemble Model with Attention Mechanism for Precise Classification of Intracranial Hemorrhages in CT scans using Hounsfield Units due to Acute Head Trauma. Artificial Intelligence in Medicine, Elsevier.
Research Interest
- Computational Neuroimaging
- Brain Disease Modelling using Markov Chain Monte Carlo
- Computational Medicine – Computational Genomics, Computational Molecular Medicine, Computational Anatomy, Computational Physiological Medicine, and Computational Healthcare
Current Research Project(s)
- Ensemble Model for Real-Time Monitoring of Waterborne Gastrointestinal Pathogens in the Eastern Cape Province, South Africa.
- Computational Neuroimaging: Deep Ensemble Model with Attention Mechanism for Precise Classification of Intracranial Hemorrhages in CT scans using Hounsfield Units due to Acute Head Trauma
Conferences & Chapters
- Optimized K-Means Clustering Algorithm using an Intelligent Stable-plastic Variational Autoencoder with Self-intrinsic Cluster Validation Mechanism. In Proceedings of the 2nd International Conference on Intelligent and Innovative Computing Applications (pp. 1-11). ICONIC. Plaine Magnien, Mauritius. Available in the ACM Digital Library. https://doi.org/10.1145/3415088.3415125
Research Quality
Social Media and Academic Networking Tools
https://www.researchgate.net/profile/Rufus-Gikera
