Research Discipline(s)
Brief Biography (English)
Professor Mattia Vaccari was born in Montebelluna, Italy. He is an Italian Citizen and a South African Permanent Resident. He received a Diploma of Scientific Studies from the ”Primo Levi” Scientific High School of Montebelluna (July 1993, 60/60), an MSc in Physics from the University of Padova (17 July 2000, 110/110 cum laude) and a PhD in Space Science and Technology from the University of Padova (21 May 2004). From September 2022 to date he has been employed as eResearch Director and Research Professor of Astroinformatics within the DVC Office for Research & Internationalisation at the University of Cape Town (UCT). In this role, he leads UCT's eResearch Centre and carries out Astroinformatics research at the Inter-University Institute for Data Intensive Astronomy (IDIA) where he leads the HIPPO project.
Prof Vaccari's research activity has mostly been concerned with multi-wavelength observational studies of long-wavelength extragalactic populations detected by (far-)infrared, (sub-)millimeter and radio surveys, using number counts, luminosity functions and spectral energy distributions to probe galaxy formation and evolution through cosmic time. Early in his career, he has been involved in several projects involving data reduction and analysis at infrared (loosely defined as 1-1000 micron) wavelengths as well as science planning and simulations for space missions operating at these wavelengths. He has also worked on several space-based instrumentation and related software development projects, both in their planning and proper development phases. More recently, he led observational projects at both optical and radio wavelengths but also developed a ”data fusion” framework to make the most of future extragalactic surveys in a multi-wavelength context. Most of his work has been carried out within a number of large survey projects undertaken by international consortia, where he has developed a strong interest in techniques for the automated reduction and statistical analysis of large datasets on one hand and in software development and science planning for new instrumentation on the other.
