Zulkarnain Hassan is a senior lecturer at Faculty of Civil Engineering Technology, Universiti Malaysia Perlis (UniMAP). He graduated and holds a Ph.D. in Civil Engineering from Universiti Teknologi Malaysia. He is also a member of the International Association of Hydrological Sciences (IAHS), Board of Engineering Malaysia (BEM), and Malaysian Hydrological Society (MHS).

Zulkarnain focused on the research to improve the prediction of flood characteristics through the development of matrix based models, the use of data from general circulation models for climate change, and through the better characterization of risk and uncertainty. His research interests include:

  • hydrology and water resources;
  • artificial intelligence;
  • optimization;
  • climate change; and
  • risk and uncertainty analysis.

 

Recent Publication:

1. Hassan, Z. (2020). An Integration Based Optimization Approach (ABC and PSO) for Parameter Estimation in BLRP Model for Disaggregating Daily Rainfall. Pertanika J. Sci. & Technol., 28 (1), 385-402. SCOPUS
2. Hassan, Z., Rosdi, S.Z., Kamarudzaman, A.N., Abdul Rahim, M., and Md. Ghazaly, Z. (2019). Comparison of Artificial Neural Network and Support Vector Machine for Long-Term Runoff Simulation. IOP Conference Series: Earth and Environmental Science, 476(2020), 012119. DOI: 10.1088/1755-1315/476/1/012119