Hello, I'm
João Pedro Fontes
Backend Engineer · Python · AWS / GCP
I specialise in building scalable backend systems and robust RESTful APIs. Currently at @LokaHQ designing robust RESTful APIs and cloud-native infrastructure with FastAPI, AWS, and GCP. My background in AI research at the University of Minho gives me a strong foundation for data-intensive problems — with work published in Computers in Biology and Medicine and presented at the European Congress of Radiology.
Career
Experience
Loka Inc.
Advanced Backend Engineer
Sep 2024 – PresentDeveloping scalable and maintainable backend systems using Python and FastAPI. Designed and implemented robust RESTful APIs with a focus on high performance, reliability, security, and observability. Utilized Docker and cloud technologies in production environments while providing on-call support.
Swoove Studios
R&D Engineer
Jul 2023 – Aug 2024Within the R&D department, played a key role in elevating animation quality through innovative AI solutions. Leveraged Python expertise to develop advanced Pose Estimation and Reconstruction tools, utilizing PyTorch and integrating with Procedural Animation in Unity. Engineered a cutting-edge animation search system by combining Python-based NLP with Azure.
Accenture Portugal
Senior Analyst
Jan 2023 – Jun 2023Promoted to Senior Analyst. Continued on the Worten engagement, contributing to the order tracking system built on Golang and AWS. Drove system improvements and provided on-call support during the final phase of the project.
Analyst
Sep 2021 – Dec 2022Consulted across two clients: Sky (Sep 2021 – Dec 2021) in telecommunications and Worten (Jan 2022 – Dec 2022) in retail. Gained hands-on Java backend experience, managed a critical order tracking system using Golang and AWS, and contributed to system enhancements with on-call troubleshooting support.
CCG/ZGDV Institute
Senior AI Researcher
Oct 2018 – Jul 2021Led AI research within the CVIG department on EU-funded projects focused on Industry 4.0 and intelligent systems. Developed production-ready Python solutions bridging academic research and real-world applications. Mentored incoming research fellows and shaped the team's AI methodology across multiple project domains.
Research Fellow
Oct 2017 – Oct 2018Joined as a Research Fellow in the CVIG department contributing to EU-funded projects at the intersection of AI and criminal investigation. Built early Python-based ML pipelines and collaborated with multidisciplinary research teams.
Academic Background
Education
Ph.D. in Information Systems and Technology
University of Minho
Focus: Development of Quantitative Imaging Biomarkers for cancer diagnosis and monitoring, applied to breast cancer.
Thesis: "A Framework for the Development of Quantitative Imaging Biomarkers for Cancer Research"
M.Sc. in Informatics Engineering
University of Minho
Specializations: Artificial Intelligence, Business Intelligence, Parallel and Distributed Computing.
Thesis: "Intelligent Medical Image Analysis: A Deep Learning Approach to Breast Cancer Diagnosis"
B.Sc. in Informatics Engineering
University of Minho
Core curriculum covering programming, algorithms, computer architecture, databases, and advanced mathematics.
Expertise
Tech Stack
Core Competencies
Programming Languages
Frameworks & Tools
Cloud & DevOps
Work
Portfolio
Credentials
Certifications
AWS Certified Cloud Practitioner
Amazon Web Services
Foundational understanding of IT services and their uses in the AWS Cloud. Demonstrated cloud fluency and foundational AWS knowledge.
Research
Publications
Deep Learning Framework for Breast Cancer Subtypes Detection and Diagnosis
Biomedical Signal Processing and Control
A Comprehensive Framework for Detecting and Diagnosing Breast Cancer Phenotypes in MRI
European Congress of Radiology (ECR), Poster C-24782
Accurate Phenotyping of Luminal A Breast Cancer in Magnetic Resonance Imaging: A New 3D CNN Approach
Computers in Biology and Medicine, vol. 189, 109903
An Innovative Faster R-CNN-Based Framework for Automated Detection of Breast Cancer Pathological Lesions in MRI
Journal of Imaging, vol. 9, no. 9, 169
Deployment Service for Scalable Distributed Deep Learning Training on Multiple Clouds
11th Int. Conference on Cloud Computing and Services Science (CLOSER), 135–142
Representation Learning Approach to Breast Cancer Diagnosis
European Congress of Radiology (ECR), Poster C-2062
AGATHA: Face Benchmarking Dataset for Exploring Criminal Surveillance Methods on Open Source Data
2018 Int. Conference on Graphics and Interaction (ICGI), 1–8
About
Additional Info
Languages
Licenses