Nicholas Njiru is an Assistant Lecturer in the Faculty of Computing and Information Technology and a Subject Matter Expert in ICT, with over 8 Years university teaching experience. His career ambition is to climb to the highest level of Computer Science and Technology management through hard work, experience and pursuit of academic and professional excellence in computing, research, and management. I love being able to learn new technologies and adapt to new working environments. My goal is to be in a place where I will grow and take part in creating solutions that can positively impact society.
Academic Qualification:
PhD in Computer Science and Informatics, University of the Free State (Ongoing)
Master of Science Degree in Computational Intelligence, University of Nairobi.
Bachelor of Science in Computer Science(1st Class honors), Catholic University of Eastern Africa.
Professional Qualifications
Certified Information Communication Technologists,KASNEB Part III Section 6)
IBM Big Data Engineer Certification
Huawei Certified Academy Instructor-HCAI (Artificial Intelligence)
Huawei Certified ICT Associate-HCIA (Artificial Intelligence)
Membership of Professional Bodies or Associations
Certified ICT Technologists of Kenya
Member of Digital Communication Network Africa
Research Interest
Artificial Intelligence, Machine Learning and Deep Learning
Computer Vision
Big Data,Data Science, Data Mining and Data Visualization
Graph Networks, Analytics and Visualization.
Programming(Mobile, Web and Desktop)
Natural Language Processing and Speech Recognition
Publications
Nicholas Njiru, Elisha Opiyo. Clustering and Visualizing the Status of Child Health in Kenya: A Data Mining Approach. International Journal of Social Science and Technology, Centre for Promoting Knowledge (CPK), UK, 2018, 3 (6).
Namaswa, S., Njiru, N., Et Al. (2021) “Application of Data-Driven Discovery Machine Learning Algorithms in Predicting Geothermal Reservoir Temperature from Geophysical Resistivity Method”, Journal of Transactions on Machine Learning and Artificial Intelligence, 9(4), pp. 1–12. Doi : 10.14738/tmlai.94.10281.
