Dr Yabebal Fantaye

Dr Yabebal Fantaye holds the ARETÉ Junior Research Chair in Applied Statistical Methods, Cosmology and Big Data based at AIMS South Africa. He did a BSc degree in Physics and Math at Addis Ababa University, Ethiopia, and completed his Honours and Master’s degree at the UCT through the National Astrophysics and Space Science Program (NASSP). For his PhD he went to the school for advanced studies (SISSA) in Trieste, Italy. Before taking the ARETÉ Chair position in June 2016, he was a postdoctoral researcher for one year at the University of Oslo, Norway, and for three years at the University of Rome Tor Vergata, Italy.

His current work is mostly investigating the statistical properties of the Universe using the Cosmic Microwave Background (CMB) data from the Planck satellite. He also works on Big Data analysis and has contributed different software to the public.

Dr Fantaye sees the AIMS ARETÉ Research Chair position as an ambitious, unique, forward-looking, and generous position which he says he is delighted to hold. He further highlights that “with Africa hosting world-leading initiatives like the Square Kilometer Array (SKA), Africa is positively transforming itself in all dimensions.” With his background in Cosmology, Big Data and Machine Learning he has indicated that what excites him about the AIMS ARETÉ Research Chair position is the opportunity to work in organisations like AIMS and in close collaboration with institutions in his home country Ethiopia, while building and fostering global research collaborations: “This provides a unique platform for me to be part of Africa’s transformation and an opportunity to make a real difference through research within the mathematical sciences.

As the ARETRÉ Chair, he will train Young African scientists on Big Data techniques, which are indispensable tools to efficiently manipulate and mine cutting-edge astronomical data from African large radio experiments for e.g. MeerKat, SKA. His other main interest is leveraging Astronomy data skills to help extract key insights from complex African social data.