Research Assistant


Pillar / Cluster: Engineering Systems and Design


I graduated in Environmental Engineering (MSc and BSc) at Politecnico di Torino in 2007, and after a short experience as an IT consultant, I returned to my Alma Mater to work as a Research Assistant for the Department of Environment, Land, and Infrastructure Engineering and the Department of Electronic and Telecommunications. My work was mostly concerned with hydro-meteorological and air quality forecasting using data-driven modelling and artificial intelligence tools. In 2010 I started my PhD in Coastal and Hydraulic Engineering at the Department of Civil and Environmental Engineering at Hong Kong Polytechnic University, and I expect to defend my thesis in mid-2015. My PhD research is focused on the improvement of data-driven rainfall-runoff modelling techniques using swarm optimisation algorithms. I joined SUTD in early 2015, where I will be extending the work I have done on data-driven hydrological modelling, as well as conducting research on the security of water distribution systems.


  • Ph.D. in Coastal and Hydraulic Engineering, Hong Kong Polytechnic University (due in 2015)
  • M.Sc. in Environmental Engineering, Politecnico di Torino (2007)
  • B.Sc. in Environmental Engineering, Politecnico di Torino (2004)


  • University of New South Wales, School of Civil and Environmental Engineering, Sydney (AUS) (2013)
    Visiting Research Student
  • Politecnico di Torino, Department of Electronics and Telecommunications (DET), Turin (Italy) (2010)
    Research Assistant
  • Politecnico di Torino, Department of Land, Territory and Infrastructures (DIATI), Turin (Italy) (2008/2009)
    Research Assistant

Research Interests

  • Use of machine learning and global optimisation algorithms for the development of data-driven hydrological models
  • Hydrological modelling and forecasting
  • Global rainfall and runoff predictability
  • Analysis of water distribution systems


  • Taormina, R., & Chau, K. W. (2015). Data-driven input variable selection for rainfall-runoff modeling using binary-coded particle swarm optimization and Extreme Learning Machines. Journal of Hydrology (in press). doi:10.1016/j.jhydrol.2015.08.022
  • Taormina, R., Chau, K. W., & Sivakumar, B. (2015). Neural network river forecasting through baseflow separation and binary-coded swarm optimization. Journal of Hydrology (in press). doi:10.1016/j.jhydrol.2015.08.008
  • Taormina, R., & Chau, K. W. (2015). ANN-based interval forecasting of streamflow discharges using the LUBE method and MOFIPS.Engineering Applications of Artificial Intelligence, 45, 429-440. doi:10.1016/j.engappai.2015.07.019
  • Karakaya G., Galelli S., Ahipasaoglu S.D., & Taormina R. (2015). Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy Approach. IEEE Transactions on Cybernetics. doi: 10.1109/TCYB.2015.2444435.
  • Taormina, R., & Chau, K. W. (2015). Neural network river forecasting with multi-objective fully informed particle swarm optimization. Journal of Hydroinformatics, 17, 99-113. doi: 10.2166/hydro.2014.116
  • Taormina, R., Chau, K. W., & Sethi, R. (2012). Artificial neural network simulation of hourly groundwater levels in a coastal aquifer system of the Venice lagoon. Engineering Applications of Artificial Intelligence, 25(8), 1670-1676. doi:10.1016/j.engappai.2012.02.009


  • Hong Kong Ph.D. Fellowship, Research Grants Council (RGC)/University Grants Committee (UGC) of Hong Kong (2010 – 2014)
  • Full Tuition Fee Waiver, Hong Kong Polytechnic University (2010 – 2014)
  • Thesis Abroad Scholarship, Politecnico di Torino (2007)
  • Student Merit Scholarship, ARCA Enel (2002-2003)