Dr Inger Fabris-Rotelli is a senior lecturer in the Department of Statistics in the Faculty of Natural and Agricultural Sciences. Dr Fabris-Rotelli’s specific research focus is Spatial Statistics for Image Processing. This is a niche area as traditional spatial statistics focuses on geographic and GIS remote sensing data mostly. While computer vision does take into account spatial relationships, it has not taken complete advantage of the theoretical strengths in the field of spatial statistics. Her research stems from the machine learning and big data aspects of spatial statistics for image processing, dealing with the big data elements that theoretical spatial statistics has not fully acquired at this stage. Her postgraduate studies were in Applied Mathematics with a focus on image processing, with a new contribution to machine learning achieved by the multidimensional LULU operators and the resulting DPT. This provides a theoretical grounding to the development of new applications using it. Combining spatial statistics, which is traditionally applied to GIS data, provides a second layer of novelty, most recently shown in 2018 publications. Post her PhD she has developed further her skills in spatial statistics with the specific angle of applying in image analysis. In addition, this niche research area allows for expansion into deep learning, an essential element of 4IR. Deep learning is a quickly developing field and is very effective, however, the approach is output based and not theoretically based on the understanding of how it achieves classification results. Dr Fabris-Rotelli’s contribution to machine learning using spatial statistics is theoretical and implementable in all cases, as is visible in her research outputs. Her research aims to provide theoretical understanding of deep learning algorithms. Dr Fabris-Rotelli graduated with her PhD in April 2013. She has an extensive postgraduate student supervision record and particularly enjoys postgraduate supervision and believes a full research process is not successful without a large team inspiring each other and sharing knowledge effectively. Her research in spatial statistics has acquired industry collaborations with Lightstone and ESRI South Africa, for research topics and postgraduate student support doing industry relevant research and gaining valuable work experience through an academics. Further, her nomination in 2015 to feature as one of the emerging woman in science in the DST publication in 2017 (link), is an acknowledgment of her standing in the academic environment, especially in a field such as statistics and mathematics which does not have traditional tangible outputs to general society and media which are present in other fields of science such as medicine. Dr Fabris-Rotelli is an early career academic who has demonstrated leadership potential as a young academic, with administrative and academic leadership roles in her department and at the faculty level. She acted as a panelist to the South African Woman in Mathematical Sciences Association workshop on Harnessing the leadership and agency of women in the field for the transformation agenda in June 2019. In 2018 she was confirmed as a Tuks Young Researcher Leadership Program fellow in recognition of my leadership potential as an academic. She believes undergraduate teaching should be effective, stimulating, and inspiring, but through teaching students to work in a dedicated way and achieve their potential for problem-solving. Modern modalities of teaching are important to take up with the developments in the young generation. Through her roles within her department - teaching and learning, postgraduate committee, undergraduate advisor, honours research report co-ordinator – she provides a strong contribution to the growth of programs with the university and further nationally through exposure to the other universities. She has had two children since completing her PhD, taking maternity leave in 2013 and 2015, adamant that the role of a woman is nurturing and intellectual, wearing both hats.
