Daniel Felipe Perez Ramirez

Daniel current research interest focuses on applying machine learning for solving combinatorial optimization problems in the context of resource management of networked systems, with emphasis on scalability and generalization capabilities. He is currently working on the SSF project 'Instant Cloud Elasticity' and on the Horizon 2020 AI@Edge project.

He holds a B.Sc. in mechanical engineering and a M.Sc. in Robotics, Cognition, Intelligence with emphasis on cognitive systems and machine learning from the Technical University of Munich (TUM), Germany.

He joined RISE Research Institutes of Sweden AB in 2019 as a research engineer in Stockholm. In 2020, he started a Ph.D. under supervision of Prof. Dejan Kostic and Prof. Magnus Boman.
Previous to RISE, he worked on applied machine learning for the automotive industry, knowledge representation and sensor integration for robotics applications, and agile methods for product development.