Dr. Kinyua Gikunda

Designation: CoD IT – Lecturer
Contact: 0724381702
School: School of Computer Science and Information Technology
Department: IT
Email: patrick.gikunda@dkut.ac.ke

Academic Background

Qualification Institution Year
PhD. Computer Science University of Paris8 2021
MSc. Computer Science University of Nairobi 2015
BSc. Computer Science Kenyatta University 2011

Bio

Kinyua Gikunda is a Computer Science Lecturer at the DedanKimathi University of Technology. He received his BSc (Computer Science) in 2011 from Kenyatta University, MSc (Computer Science) in 2015 from the University of Nairobi, and Ph.D. (Computer Science) from the University of Paris8. His research area includes Machine Learning with a focus on deep optimization methods. His specific expertise is in Active Learning, Transfer Learning, and data-driven analytics solutions.He has recently worked on applying these approaches tointelligent farming, weather, and agricultural pest control. His newest research areas include the Carbon Footprint of Artificial Intelligence and Disaster Risk Reduction.

Areas of Expertise

  • Business Analytics
  • Machine Learning
  • Active Learning in AI
  • Transfer Learning
  • Data drivel application systems
  • Internet of things

Publications

  • Wanza, I., Kamuti, I., Gichohi, D., & Gikunda, K. (2022). The impact of Twitter on political influence on the choice of a running mate: Social Network Analysis and Semantic Analysis–A Review. arXiv preprint arXiv:2208.00479.
  • P. Gikunda and N. Jouandeau, “Homogeneous Transfer Active Learning for Time Series Classification,” 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA), 2021, pp. 778-784, doi: 10.1109/ICMLA52953.2021.00129.
  • Kinyua, P., &Jouandeau, N. (2021, September). Sample-Label View Transfer Active Learning for Time Series Classification. In International Conference on Artificial Neural Networks (pp. 600-611). Springer, Cham.
  • Gikunda, P. K., &Jouandeau, N. (2020). Cost-based budget active learning for deep learning. arXiv preprint arXiv:2012.05196.
  • Gikunda, P. K., &Jouandeau, N. (2020, September). Budget active learning for deep networks. In Proceedings of SAI Intelligent Systems Conference (pp. 488-504). Springer, Cham.
  • Gikunda, P. K., &Jouandeau, N. (2019, July). State-of-the-art convolutional neural networks for smart farms: A review. In Intelligent computing-proceedings of the computing conference (pp. 763-775). Springer, Cham.

Research

  • The Fall Army Worm Identification and Mitigation in Kenya
  • Carbon Footprint of High-Performance Computing
  • ModelingDisaster Risk Reduction in agricultural processes

Research Interests

  • Active Learning in AI
  • Transfer Learning