André Baltazar
“We would like to nominate André Baltazar for his achievements in the field of mechatronics, particularly within the TRIBE LAB, as well as for the exemplary organisation of the event Synergy Day by INESC TEC 2025. The success of this year’s edition – which involved multiple centres and over 100 participants, with activities both in the auditoriums and in the vineyards of UTAD – required a high level of planning, coordination, and execution. All this work was carried out with professionalism, dedication, and quality, which is why he deserves this nomination.”
– CRIIS coordinators
The coordinators mentioned the results achieved in the mechatronics area of TRIBE LAB; could you tell us more about your activities in terms of developing projects/solutions/innovations in this field? Is there any result or technology you would like to highlight?
The mechatronics area at TRIBE LAB is essential for the design and development of our prototypes, as we always seek to create solutions from the ground up. This approach allows us to control factors like cost and complexity, making it easier to transfer the technology to the market. As to the results, I would highlight Modular-X, developed in just three months at the end of last year to be presented at FIRA 2025. We are currently working on the prototype of a grape harvester, which began with design thinking sessions and contributions from the entire team. The project is now in an advanced stage, and we expect to carry out the first tests and validations later this year.
You were involved in organising Synergy Day, an event focused on the agricultural, wine, and forestry sectors. How do you assess this initiative? And how important is it for strengthening the role of the institution in these fields?
The Synergy Day by INESC TEC 2025 was an event designed to showcase the latest results of our research and technological development, focusing on the application of robotics, Artificial Intelligence (AI), and the Internet of Things (IoT) in the wine sector. It was a full-day event: in the morning, an expository session with several distinguished speakers in the field, followed in the afternoon by an exhibition and demonstration of various robotics and IoT prototypes developed by TRIBE. This format brings together research institutions, technology companies, and end users in the same space, creating an excellent opportunity for knowledge sharing. The event also included contributions from colleagues in other INESC TEC centres, positioning it as a very important occasion for reinforcing INESC TEC’s role in this sector.
What aspects of your job do you enjoy the most?
Making things happen in very different contexts: from managing the mechatronics area, to organising events, to more hands-on tasks in the lab or in the field.
How do you comment on this nomination?
This is recognition that I must share with the entire TRIBE LAB team. Our team spirit is what sets us apart and enables us to reach ambitious goals. No one builds a Modular-X in three months, or organises an event with 100 participants, without having a fantastic team alongside them.
Ricardo Sousa
“We’d like to nominate Ricardo Sousa for his dedication and significant contribution to CRIIS’ activities, particularly in mobile robotics, where he has played an important role in improving localisation and navigation solutions for robots. Even while working on his PhD thesis, Ricardo has been involved in project activities, namely in managing the GreenAuto project, as well as in Produtech R3 (planning, preparing, and carrying out demonstration activities). He never fails to support his colleagues with meaningful, well-founded contributions in areas beyond the scope of his own research.”
– CRIIS coordinators
You have been actively involved in developing solutions in mobile robotics; could you give us an example of your recent work, or highlight a project/technology you consider particularly relevant?
The project linked to my PhD, which is directly related to one of the developments planned under PPS18 of the GreenAuto project, focuses on long-term localisation and autonomous navigation of mobile robots. Traditionally, mobile robots rely on a static representation of the environment. If the environment is dynamic – with people moving around, or objects such as boxes and pallets being relocated – the robot may become inoperable, unable to localise itself, and consequently unable to navigate autonomously or carry out its assigned tasks.
My PhD focuses on developing methodologies to make robot navigation more robust in dynamic environments, whether through perception of dynamics using ray tracing, generating maps that reduce the impact of environmental changes, or maintaining and updating the representation of the environment over time.
You also participate in the GreenAuto and Produtech R3 projects. What type of activities do you carry out in these initiatives? Are there any results, potential, or differentiating factors you would like to highlight?
Yes, I participate in both projects. In GreenAuto, and in addition to the PhD work related to long-term localisation and mapping, I explore aspects like 3D localisation, multimodal perception, and detection of metal boxes in the automotive industry. One interesting result of this project was a study we carried out to evaluate the performance of different 3D LiDAR-based SLAM algorithms. This required the creation of a dataset – IILABS 3D: iilab Indoor LiDAR-based SLAM Dataset – to benchmark algorithms under the same conditions. We observed that 3D LiDAR-based SLAM algorithms that incorporate Inertial Measurement Unit (IMU) data tend to achieve better results than those relying solely on 3D LiDAR.
In Produtech R3, I have worked with CRIIS colleagues on developing an algorithm for pallet detection using RGB-D cameras and on automating pallet transport in intralogistics operations with mobile robots. The algorithm uses machine learning models for RGB image segmentation and processes the point cloud from the depth channel to estimate the pallet’s pose relative to the camera.
One differentiating factor of this technology compared to other solutions in the market and literature is the fact it relies on a single RGB-D camera – potentially a low-cost one -, without considering any specific camera model, making it compatible with different RGB-D cameras on the market. Finally, I would also highlight my involvement in an initial study at CRIIS, in collaboration with NOS, for the remote control of mobile robots using NOS’ 5G network infrastructure installed at iiLab.
What aspects of your job do you enjoy the most?
Applied scientific research in real-world contexts. Since joining CRIIS, beyond the encouragement of fundamental research, there has always been an emphasis on applying our work in practical cases and potential industrial collaborations – whether in academic contexts (BSc, MSc, PhD) or institutional ones (research projects). While this innovation and real-world testing bring challenges, it is precisely these challenges that motivated me, after my master’s degree, to pursue my PhD at INESC TEC.
How do you comment on this nomination?
First, I would like to thank the CRIIS coordinators for the nomination and recognition of my work, as well as for the support they have given me in my professional development since joining INESC TEC. And of course, a special “thanks” to all my CRIIS colleagues, with whom I have the pleasure of working and collaborating every day – and for all their support as well.
Rita Vieira
“C-BER would like to nominate Rita Vieira; since joining our team in 2023, first as a research fellow, then during her master’s thesis, and later as a team member within the CARE-IN-HEALTH project, Rita has shown exemplary performance and great ability to adapt to new challenges, contributing significantly to the team’s progress and to various projects. We also highlight her role in the s2IO, SmartDBS, and iHandU projects (with important technical support provided to the start-up Insignals Neurotech), as well as in several activities related to AI4LUNGS and WeSENSS. In all these initiatives, Rita has stood out for her R&D skills, her work in developing and applying technologies, and the innovative ideas she brings.”
– C-BER coordinators
Your contributions across different projects were highlighted. Could you tell us more about each of them, and briefly describe the activities you carried out in each case?
Since joining the team, I have had the opportunity to collaborate on several projects, some of which are very different in nature. In the CARE-IN-HEALTH project, we are developing a point-of-care solution for biomarker analysis, aimed at improving the efficiency of primary healthcare.
In the SmartDBS and iHandU projects, I was involved in data collection, technology development, monitoring algorithms, and device synchronisation for Parkinson’s patients undergoing neurostimulation, in collaboration with São João Hospital. More recently, I have provided technical support mainly for the mobile applications in the AI4LUNGS and WeSENSS projects.
Since these projects are quite distinct, with specific goals and outcomes, what are the main challenges you have encountered in your work? How do you balance playing such different ‘roles’?
Working on such varied projects can be very challenging. Balancing different scientific areas, each with specific context, goals, and deadlines, requires a great deal of adaptability and resilience. To balance these roles, I try to stay well organised, set priorities, and above all, learn to adapt quickly to new contexts and technical requirements. Team support and multidisciplinary collaboration have been crucial in enabling me to perform different tasks.
Is there any project, technology, or solution you would like to highlight in terms of differentiating factor, impact, or even for more personal reasons?
I would like to highlight iHandU, for the clinical relevance and potential direct impact on the quality of life of patients with Parkinson’s. It is a clear example of how research can be transferred into a practical solution with added value for society. We have already had the opportunity to involve patients with the technology, and the feedback was very positive, which further motivates us to continue improving this solution.
What aspects of your job do you enjoy the most?
What motivates me the most is the possibility of working on technologies that can have a real impact on people’s health. I also enjoy the diversity of tasks – from programming to collecting data and engaging with patients in hospitals. Although this can be very challenging, it allows me to improve both scientifically and personally.
How do you comment on this nomination
I would like to thank the team for this nomination, for their trust, and for their support. I perceive it not just as individual recognition, but as a reflection of the team’s collective work, which has been essential for my evolution.
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