Apr 2023 – Jun 2023 · 2 mos · Remote

• As a consultant for Skibby, I specialize in AI-related software development aimed at assisting engineers and stakeholders in analyzing extensive documentation. 👩‍💻 My role involves leveraging advanced technology to enhance the efficiency and accuracy of data processing, enabling a streamlined and effective approach to document analysis.🚀 By harnessing the power of artificial intelligence, I contribute to Skibby's mission of providing an enterprise-ready back-office automation solution tailored specifically for construction companies.🏗️

Oct 2022 – Mar 2023 · 5 mos · Munich, Bavaria, Germany

• ✔️ Simulation of industrial components using Simulink;
• ✔️ Data Mining manufacturing use case using Python;
• ✔️ Responsible for a project of MATLAB / Simulink simulation of a Robot-like system;
• ✔️ Responsible for the Data Mining-related lectures.

Jul 2022 – Mar 2023 · 8 mos · Porto, Portugal

• 🚀 Designing mechanical components;
• 🚀 Solving mechanical engineering-related issues concerning the project;
• 🚀 Simulations and lab experiments.

Jul 2022 – Jul 2022 · 0 mo

• As a monitor of the Junior University program, I am responsible for a hands-on activity for two weeks for High-School students related to IoT

Jun 2022 – Oct 2022 · 4 mos · Porto, Portugal

• Porto Space Team aims to be a group of development and research on topics related to Space and to be an opportunity for collaboration.
• Responsibilities: to create conditions for the students to do Space-related activities as a first-time experience; to supervise and assure the coordination between departments exists; to plan and assure the execution of the tasks.
• Achievements: more than 90 students interested in Space engaged in the team; 2 main projects; more than 4 main partners; formation of more than 15 departments.

Apr 2022 – Sep 2022 · 5 mos · Porto, Portugal

• During my fellowship, I have been able to perform algorithmic development of optimization approaches based on Particle Swarm Optimization and its hybridizations in Fortran and Python, in order to solve multi-objective optimization problems. The following is a list of tasks I am currently working on: 1. a literature review paper concerning optimization algorithms and recent applications in composite structures; 2. papers concerning a novel methodology of applying PSO based on the concept of elitism; 3. papers concerning a hybridization approaches of hybridization techniques

Jan 2022 – Jan 2022 · 0 mo

• The Online CubeSat Concurrent Engineering Workshop 2022 is an ESA Academy training session during which university students are introduced to the concurrent design of a CubeSat mission. Guided by ESA experts, the students learn to use the Open Concurrent Design Tool and identify design drivers. Divided into teams, they first create a subsystem concept to later achieve an already identified mission concept, function tree and product tree, using concurrent engineering. The workshop helps to better prepare the university students that are planning to embark on a CubeSat project or are at the early stages of one.

Oct 2021 – Jul 2022 · 9 mos

• During the academic year 2021/22, I was responsible for coordinating the Teacher In-Service Program of IEEE UP SB, with the following numbers (variation in parenthesis related to previous records of the program):
• Organization of more than 17 activities (+183%);
• Collaboration with more than 12 schools (+100%);
• Participation of a total of 13 IEEE UP SB students (+63%);
• A total attendance of more than 800 elementary- and high-school students (+718%);
• A first-time collaboration between TISP and a research lab.
• All the numbers mentioned above are an all-time record. Some organizational difficulties happened, not only due to covid-19 but also due to the late start of academic activities.

Oct 2020 – Sep 2021 · 11 mos

• During this period, I was responsible to help the Student Branch members with their tasks related to IEEE; to debate issues concerning the covid-19 pandemic, members online interaction and more general topics. I was the coordinator of the second "Fire Department" event of 2020/21, where students join to help each other with their academic projects and studying for the exams. This edition had +111% of participating students (74) compared to the previous edition (35).

Oct 2019 – Oct 2020 · 1 yr

• I was responsible for the foundation of AESS chapter in IEEE UP Student Branch since it would allow more students from different areas to participate and to be active members in IEEE activities. AESS was the group where most IEEE UP SB members worked, during my coordination (23 out of 54) and at the beginning of the next academic year, after my AESS coordination (12 out of 31). I was responsible for the project Tarvos during my leadership. Tarvos aims to develop a small rocket with 3D printing components, allowing the growth of knowledge in this field. With this project and visits to different research units at the University of Porto, I took an important role in the growth of IEEE UP SB activity even during the covid-19 pandemic.

Jan 2018 – Sep 2021 · 3 yrs 8 mos

• The program consists of going to middle and high school to present the activities which are usually done at the University of Porto, especially related to Engineering courses. Aiming to encourage those students to gain interest in technology, programming activities and games were done in those activities.

Oct 2017 – Sep 2019 · 1 yr 11 mos

• At the beginning of my newbie phase in the IEEE UP Student Branch, I did some volunteering activities and helped my colleagues in the preparation of workshops and conferences. Also, I was the lecturer of some MATLAB workshops inside and outside of the University of Porto.

Sep 2021 – Oct 2021 · 1 mo · Aachen, North Rhine-Westphalia, Germany

• Prediction of Workpiece Quality in Fine-Blanking
• Vorhersage der Bauteilqualität für das Feinschneiden
• Digitalization and initiatives such as Industry 4.0 enforces the transition from analog process execution to the development of cyber-physical manufacturing systems that incorporate data collection and analysis to monitor and optimize manufacturing systems and processes. As a preliminary, traditional manufacturing systems, stamping process need to be equipped with sensor systems to acquire different types of data about the process. The conversion from data into informative values turns out to be a challenging aspect of cyber-physical systems with regard to the structure and amount of data that is available. The fine blanking processes in the context of an Internet of Production is considered as a use case to research the potential of increasingly available data. It is necessary to analyze the relationship between process parameters (such as material properties, temperature and other operation conditions) on a Punch-to-punch basis as well as general trends with regard to the force signals. Hence, an in-depth analysis of cyclic signals per-punch and parameters is essential for any fine blanking system. This thesis works with the feature space of punch signals and the feature space of material properties.
• The goal of this project thesis was to develop an accurate prediction model for fine-blanking workpiece quality feature, the die roll, and investigate the relationship of force signals to the resulting quality of the workpieces. Next to the shearing surface quality, the die-roll width and depth are one of the main quality issues in components produced in a fine blanking process. The data used in this work is obtained from four experiments executed on a fine-blanking press equipped with sensors to acquire the three important process forces, namely punch force, counter-punch force and blank-holder force.

Mar 2021 – Jun 2021 · 3 mos

• The project consists of building a prediction model with the highest accuracy on the quality prediction of production line parameters, using the data retrieved from sensors. General Machine-Learning techniques and other Data Science-related knowledge are used for experiments for the accomplishment of the results.
• Using Sequential Feature Selection (1 feature) and Random Forest (RF) with 50 trees were enough to improve significantly R2-scores against AutoML on regression tasks (task 1: 1 against almost 0.5; task 2: 1 against almost 0.4; task 3: 1 against almost 0.85; task 4: 1 against almost 0.98). On segment prediction (classification tasks), Recursive Feature Elimination with Cross-Validation (RFECV, 1 feature) and RF turned true all the false classifications of AutoML (+100%). Knowing the feature to select, all the models are now created quicker than one millisecond, whereas AutoML took 200 seconds to create less-accurate models.

Mar 2021 – Mar 2021 · 0 mo

• I attended the online "Introduction to Space Law Training Course", where general topics about space, future challenges, and general topics about the law were lectured. It had an exercise part that consisted of a United Nations debate simulation.

Oct 2020 – Mar 2021 · 5 mos · Aachen, North Rhine-Westphalia, Germany

• My work aimed to optimise the starting point position of a Kinematic Draping Simulation, using Particle Swarm Optimisation. These developments are assisted with code optimisation and Parallel Computing and data visualization for a real application is displayed in a User Interface I developed as well.

Mar 2020 – Mar 2021 · 1 yr

• Development of knowledge on Optimisation history and methodology, mainly concerning Particle Swarm Optimisation and related hybridisation with other techniques; applications in Engineering areas - literature review; programming in Matlab and Python; Gears design optimisation: new design methodologies; writing of papers for journals and University of Porto internal conferences.

Oct 2019 – Oct 2020 · 1 yr · Porto Metropolitan Area

• I was in a team caring about the high-school students' recruitment to form a team of talents before their entry into academic life. I participated in the organization of several activities for that team before its training sessions.

Jul 2019 – Sep 2019 · 2 mos · Aveiro e Região, Portugal

• Acquisition of case studies of Gas Water Heater users:
• Big Data treatment: treatment of the behaviour of GWH based on data (temperature, flow) collected from data loggers application; Matlab scripts interpretation and improvement; computational optimization.
• Analysis and correction of procedures for Durability laboratory.
• Improvement of organizational skills: meetings, 5s digital, programming automatic file organization in their directories (VBA).
• Matlab GUI interfaces creation for uniformization for scripts usage.
• Presentation of numerical analysis of data.
• Matlab validation based on VBA userforms with known information filled.
• Databases and folders update related with field tests.
• Data logger assembly: flow meters, hydraulic components, temperature sensors.
• Test request improvement for Durability laboratory, based on proceeding standard configurations.

Jun 2018 – Dec 2018 · 6 mos · Porto e Região, Portugal

• Analysis of carotid medical images;
• Code development about medical images processing;
• Numerical analysis applications;
• Computer vision;
• Writing articles;
• Work presentation/speaker.

Mar 2018 – Dec 2018 · 9 mos · Porto e Região, Portugal

• Researching works about usability/user experience;
• writing of papers.