I am a doctoral student in the CMU-Portugal dual-degree PhD program in Software Engineering at Carnegie Mellon University (CMU) and Computer Science and Engineering at Instituto Superior Técnico (IST) - Universidade de Lisboa.
I am being kindly advised by Prof. Paolo Romano at IST and Prof. David Garlan at CMU. I am currently working as graduate research assistant at Institute for Software Research (ISR) where I integrate the ABLE Group, and as researcher at IST and in the Distributed Systems Group at INESC-ID Lisboa where I am currently envolved in the CAMELOT research project.
My research and main areas of interest are focused in Machine Learning, Artificial Intelligence, Distributed Systems, Cloud Computing, Virtualization, Optimization, and Computer Networks.
Information also available on Google Scholar.
Articles in Proceedings
TrimTuner: Efficient Optimization of Machine Learning Jobs in the Cloud via Sub-Sampling.
Leveraging Subsampling Techniques to Optimize Machine Learning Jobs in the Cloud.
HyperJump: Accelerating HyperBand via Risk Modelling. Hyper-Parameter Tuning using Bayesian Optimization.
Pedro Mendes, 2021.