Nature-Inspired Machine Learning (NIMI)
Research Associate
Nature-Inspired Machine Learning (NIMI)
Tshiangomba is a Ph.D. candidate at the NIMI group and AIMS RIC funded by the Carnegie Corporation of New York, which devotes its efforts toward advancing education and knowledge to support educational activities across the world.
He received his M.Sc. in Mathematical Engineering from the University of L’Aquila in Italy, an M.Sc. of Sciences in Mathematical Science at the African Institute for Mathematical Sciences (AIMS), and a 5-year bachelor’s degree in Pure Mathematics with a major in Differential Geometry.
His current Ph.D. research focuses on using generative models to perform link prediction, build robust knowledge graph embedding models, and online learning for knowledge graphs using the idea of interacting particles to define the dynamic.
Tshiangomba Kasonsa Reagan
Research Associate
Nature-Inspired Machine Learning (NIMI)
Tshiangomba is a Ph.D. candidate at the NIMI group and AIMS RIC funded by the Carnegie Corporation of New York, which devotes its efforts toward advancing education and knowledge to support educational activities across the world.
He received his M.Sc. in Mathematical Engineering from the University of L’Aquila in Italy, an M.Sc. of Sciences in Mathematical Science at the African Institute for Mathematical Sciences (AIMS), and a 5-year bachelor’s degree in Pure Mathematics with a major in Differential Geometry.
His current Ph.D. research focuses on using generative models to perform link prediction, build robust knowledge graph embedding models, and online learning for knowledge graphs using the idea of interacting particles to define the dynamic.
Publications
Research Associate
Nature-Inspired Machine Learning (NIMI)
Tshiangomba is a Ph.D. candidate at the NIMI group and AIMS RIC funded by the Carnegie Corporation of New York, which devotes its efforts toward advancing education and knowledge to support educational activities across the world.
He received his M.Sc. in Mathematical Engineering from the University of L’Aquila in Italy, an M.Sc. of Sciences in Mathematical Science at the African Institute for Mathematical Sciences (AIMS), and a 5-year bachelor’s degree in Pure Mathematics with a major in Differential Geometry.
His current Ph.D. research focuses on using generative models to perform link prediction, build robust knowledge graph embedding models, and online learning for knowledge graphs using the idea of interacting particles to define the dynamic.
