Felipe Atenas

I am a research fellow in optimization in the School of Mathematics and Statistics of the University of Melbourne.

My research focuses on theoretical foundations for computational optimization methods to solve operations research and machine learning problems. I am particularly interested in algorithms to solve optimization problems with exploitable structures that break large-scale problems into smaller, more manageable pieces, and take advantage of the underlying properties of the models. Examples of optimization problems that fall into this category appear in statistical learning, signal processing, multistage stochastic optimization, consensus multi-agent optimization, and power systems.

Email: felipe.atenas@unimelb.edu.au

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About myself

Originally from Chile, I moved to Campinas, State of São Paulo, Brazil, to pursue my PhD in Applied Mathematics, right before the pandemic started. My PhD supervisor was Claudia Sagastizábal, with Paulo J. S. Silva as co-supervisor, both from the State University of Campinas (Unicamp). During my PhD, I visited Jonathan Ecsktein at Rutgers University.

After defending my PhD, I moved to Melbourne, Australia, to work as a postdoctoral researcher, my current job. Here, I met my new two collaborators: Matthew Tam (The University of Melbourne, Unimelb) and Minh Dao (The Royal Melbourne Institute of Technology, RMIT).