I am a data engineer with a solid background in anomaly detection, currently focused on neuroimaging. Before starting my PhD, I spent seven years refining machine learning models to enhance system security through immunity measures, leading an AI research team and contributing to several peer-reviewed publications. My interest in neurolife and psychiatric disorders led me to deepened my knowledge in the field. I’d like to develop diagnostic biomarkers and make reliable predictions of mental illnesses leveraging my expertise in anomaly detection. I had the honor of collaborating with VMware and am passionate for open-source development and Git. The ultimate goal of my doctoral work is to enhance mental health care and reduce treatment costs.
In 2021 I graduated with a master’s degree in electrical and computer Engineering from Universidade de Coimbra. With a double major in automation and computers. In 2022, I was awarded a fellowship grant to join the SAFEFOREST project (a CMU-Portugal project). My research is focused on research path and motion planners, as well as develop a system using Gazebo and MoveIt (a ROS framework) to compare several path planning algorithms that help a wheeled robot navigate through an octree representation of its surroundings.
After finishing my integrated Masters in 2021 from the University of Coimbra in Portugal and working for 8 months as a researcher, I am now starting my doctoral path with the CMU Portugal Affiliated Ph.D. Program in Electrical and Computer Engineering on forestry robotics, with a workplan entitled “Efficient Large-Scale Mapping and Path Planning in Forest Environments”.
