Manuel Causín

I'm an engineer with a strong interest in programming, machine learning, and IoT. I have developed my skills through various personal projects, including a LoRaWAN-based smoke detector and an image detection system built with a Raspberry Pi.

Colaborator Researcher at Citius (Centro Singular de Tecnologías de la Información) (2025-09 – Present)

I am part of a European project called COLLAGE (Comprehensive ML-based Analysis of Fetal Growth Trajectories), which focuses on applying AI to fetal development in order to identify early signs of potential diseases or syndromes.

• Developing software solutions for the preprocessing, training, and inference of various machine learning models based on medical imaging
• Storing the outputs in a shared database
• Contributing to the improvement of the dataset and the API that enables its access and use across the project

Curricular practices at CESGA (Centro de Superomputación de Galicia) (2024-04 – 2024-05)

I was part of the E-Learning department within the Avatiño project, where we developed a telepresence robot inspired by the European project ABILITI. During this experience, I applied my knowledge in 3D printing, computer vision, Node.js, Python, electronics, mechanical design, and networking and communications.

External practices at SISLOVE (Sistemas de Localización de Vehículos) (2023-09 – 2024-01)

During these months, I was responsible for developing the protocol parser for a geolocation device, implementing it within a Node-RED server. This included working extensively with JavaScript and Python to decode, interpret, and structure the raw data received from the device.

• Designed and maintained custom parsing flows
• Validated communication formats
• Managed message routing
• Integrated the processed data into downstream services
• Gained solid hands-on expertise with geolocation and tracking devices
• Developed robust, scalable parsers for real-time data processing

External practices at SISLOVE (Sistemas de Localización de Vehículos) (2022-06 – 2022-09)

During this period, I worked on a project focused on detecting the fill level of waste containers using computer vision techniques—both classical methods such as Canny edge detection, and deep learning models like YOLO. I also trained a custom model specifically tailored for this task.

Robotics degree in Robotics – Universidad de Santiago de Compostela (2020-09 – 2024-07)

Extracurricular courses in La rebelión de los chips: ética e inteligencia artificial – UNED (2023-07 – 2023-07)

Masters degree in IoT – Universidad de Santiago de Compostela (2024-09 – 2025-07)