About me

I am a Research Fellow (Level B) at the School of Computer and Information Systems (CIS), The University of Melbourne; and the ARC Industrial Transformation Training Centre in Optimisation Technologies, Integrated Methodologies and Applications (OPTIMA). Before joining CIS and OPTIMA in January 2022, I was a Research Fellow (Level B) at the School of Mathematics and Statistics, The University of Melbourne, from September 2017. Before that, I was a Research Fellow (Level A) at the School of Mathematical Sciences, Monash University, from March 2014. I received my Engineer’s and Master’s Degrees from the Universidad del Valle (Colombia) in 2005 and 2008 respectively; and my doctorate from The University of Melbourne in 2014.

The primary focus of my research is analysing the relationship between algorithm performance and problem structure, emphasising learning and optimisation algorithms applied to black-box optimisation (BBO) problems. In other words, I am interested in answering the questions:

• What makes a problem instance easy or hard for an algorithm?
• Is the difference in performance the result of intrinsic biases? and
• How to exploit this knowledge for the selection and design of algorithms?

While strongly related to the Algorithm Selection Problem, my work attempts to develop scientific benchmarking methodologies that move away from the status quo of competitive benchmarking. My main contribution has been to the development of the MATILDA computational engine for Instance Space Analysis. Complementing this primary focus, I am interested in developing interdisciplinary work, having published in fields as diverse as Biomechanics, Resources Engineering, Computational Biology and Corporate Social Responsibility.

I have published over 50 papers, including over 30 articles in leading journals. Moreover, I currently co-supervise six PhD students, while two PhD students have completed under my supervision.