Hi there!
I am a Geo-Information, AI and Cloud Engineer. 🛰️ 🌍 🤖
I enjoy working on hard things that matter to everyone and I like to work with people that care deeply about what they do.
Satellite imagery and geo-information broadly has an incredible potential impact on increasing transparency, efficiency and development all across the world, as long and we do it right. I intend to help make it rigth.
Here is a brief overview of my professsional experience, my education background and also some non-profits I’ve worked with over the years.
If you have any questions or remarks feel free to reach out - I am always happy to chat!
Experience
🏢 Jua.ai | November 2022 – June 2024
📌 Engineering Manager, Data team | Mar 2023 – Jun 2024
- Leading a team of 2 engineers and working closely with product.
- Ingest 30 different sources of historical weather observation data into a common data warehouse, using Zarr and Parquet (> 500 TB).
- Create live ETL pipelines for weather data using Prefect, deploying it using Pulumi in GCP.
📌 Senior Data Engineer | Nov 2022 – Mar 2023
- Using Zarr and Dask, created a pipeline to downscale weather forecasts to 1x1 km at the global level, 4x a day, using a deep learning model.
- Developed live ingestion pipelines for multiple weather data sources (reanalysis data and observation data), using AWS Step Functions.
🏢 Development Seed | August 2021 – October 2022
📌 Cloud Software Engineer
- Developed a multi cloud (AWS and GCP) and cost efficient cloud infrastructure for running deep learning based oil slick detection with Sentinel-1 images, in the entire archive, and automatically for newly available scenes. Cerulean App
- Developing an ingestion pipeline and search API that is able to handle millions of images and return similarity, at scale. Similarity Search App
🏢 UP42, an Airbus company | September 2019 – July 2021
📌 Senior Data Science Engineer | Jan 2021 – Jul 2021
- Using FastAPI to develop asynchronous micro services to estimate resource consumption of geospatial workflows.
- Developing full CI/CD pipeline for dockerized geospatial processing tools, including live and end to end tests.
📌 Data Science Engineer | Sep 2019 – Dec 2021
- Developing processing chains for geospatial data in Python with Docker.
- Build requirements for compatibility service of different geospatial processing chains.
- Conceptualise and train deep learning model for land cover classification with satellite images using TensorFlow.
🏢 Planet | April 2018 – August 2019
📌 Pre-Sales Engineer | Jul 2018 – Aug 2019
- Technical consultancy for prospective customers.
- Developing internal tools for reporting and data visualisation.
📌 Internship | Apr 2018 – Jun 2018
- Evaluate global performance of CNN for ship detection in satellite imagery using an automated approach.
🏢 Wageningen University and Research | Sep 2017 – Feb 2018
📌 Teaching Assistant
- Geoscripting
- Programming in Python
🏢 Agroop | October 2015 – August 2016
📌 Account Manager and Agronomist
- Agronomic technical assistance to customers.
- Support development team with user requirement reports.
Education
🎓 MSc Geo-Information Science | 2016 – 2019
🏫 Wageningen University and Research - WUR
cum laude, 8.6/10 average score
- MSc thesis | Potential use of unmanned aerial vehicles for estimating fruit maturity via electronic noses: Malus domestica case study - full text
- Assistant in conferences - KLV Alumni reunions, Competence 2016 and AGILE 2017
🎓 BSc Agriculture Engineering | 2012 – 2015
🏫 Instituto Superior de Agronomia - ISA, Lisbon University
14.1/20 average score
Volunteering
- Since Oct 2023: Mediator and organisation member of the Touch Rugby team – Berlin Bruisers
- Oct 2016 – Aug 2018: Public Relations Manager, Spectrum – Student Chaplaincy and Platform
- Sep 2012 - Aug 2017: Marketing and Communication Manager, Gymnastics Club of Almada
- Dec 2014 – Sept 2015: President of the Board, Agronomy Student’s Association of ISA
Publications
Inferring Ethylene Temporal and Spatial Distribution in an Apple Orchard (Malus Domestica Borkh): A Pilot Study for Optimal Sampling with a Gas Sensor, DOI:10.1007/s13580-020-00316-9
Super-resolution of multispectral satellite images using convolutional neural networks, DOI:10.48550/arXiv.2002.00580
A Comprehensive Study of the Potential Application of Flying Ethylene-Sensitive Sensors for Ripeness Detection in Apple Orchards, DOI:10.3390/s19020372