Yuhanis Yusof is a senior lecturer in School of Computing, Universiti Utara Malaysia, Malaysia. She obtained her PhD in Computer Science from Cardiff University, UK. She also holds MSc degree in Computer Science and Bachelor of Information Technology. Her research interest is broadly in data analysis and management for large scale computing. This includes data mining (discovering patterns of interest from data), data warehousing, information retrieval, digital libraries and software reuse. She is also involved in the area of Computational Intelligence, particularly in Machine Learning and Swarm Computing.

1. 1. Mustaffa, Z., Yusof, Y., & Kamaruddin, S. S. (2014). Enhanced Artificial Bee Colony for Training Least Squares Support Vector Machines in Commodity Price Forecasting. Journal of Computational Science, 5(2), 196-205. doi: http://dx.doi.org/10.1016/j.jocs.2013.11.004 (ISI-Q2 with IF:1.567 and SCOPUS indexed)
   2. Mohammed, Athraa Jasim, YuhanisYusof, & Husni, Husniza. (2016). GF-Clust: A Nature-Inspired Algorithm for Automatic Text Clustering. Journal of Information and Communication Technology, 15(1), 57-81. (SCOPUS indexed)
   3. Ahmad, Farzana Kabir, Al-Qammaz, Abdullah YOusef Awwad, & Yusof, Yuhanis. (2016). Optmization of Least Squares Support Vector Machine Technique using Genetic Algorithm for Electroencephalogram Multi-Dimensional Signals. Jurnal Teknologi, 78(5-10), 107-115. (SCOPUS indexed)
   4. Mustaffa, Z., & Yusof, Y. (2014). LSSVM Parameters Tuning with Enhanced Artificial Bee Colony. The International Arab Journal of Information Technology, 11(3). (ISI with IF:0.39 and SCOPUS indexed)
   5. Mustaffa, Z., Yusof, Y., & Kamaruddin, S. S. (2014). An Enhanced Artificial Bee Colony Optimizer for Predictive Analysis of Heating Oil Prices using Least Squares Support Vector Machines. In S. Alam, G. Dobbie, Y. S. Koh & S. u. Rehman (Eds.), Biologically-Inspired Techniques for Knowldege Discovery and Data Mining (pp. 149-173): IGI Global. (SCOPUS indexed)