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About Candidate
Location
Education
Dissertation titled 'Artificial Intelligence-Powered Classification of Flora in Vineyards'. Developed an AI-driven system using PyTorch to classify vineyard flora from a dataset of over 5,000 images, employing advanced machine learning algorithms and neural network architectures. Achieved a 96% accuracy rate in species identification and classification, earning a final grade of 19/20
• Seminar titled 'Air and Water Ǫuality in Smart Cities,' focused on the integration of IoT technologies for intelligent environmental monitoring. It received a rating of 17/20 for its presentation of innovative strategies.
Work & Experience
• Responsible for programming accurate and reliable software systems for international corporations; • Implementing applications for Android Automotive Operating System (AAOS); • Relevant role in developing an infotainment panel for the automotive sector, according to Jira user stories; • Testing and debugging applications using CANoe, with delivery on GitLab or GitHub; • Continuous troubleshooting in cooperation with international developers