PHD at Pontifícia Universidade Católica do Paraná, Brazil
Santiago Felipe Luna Romero is a prominent AI Expert and Data Scientist based in Curitiba, Paraná, Brazil. Currently a PhD Candidate at Pontifícia Universidade Católica do Paraná, his research focuses on health technology innovation. Santiago excels in Python, PyTorch, and TensorFlow, leading AI projects within smart city initiatives. As an Artificial Intelligence Engineer at Automa Vision, he spearheads the development of computer vision models for smart city applications, including drone imagery for urban feature detection. With a Master’s Degree in AI from Universidad Internacional de La Rioja and extensive experience in research and development, Santiago is passionate about applying his skills to create transformative AI architectures aligned with strategic objectives
Professional Profiles:
Googlescholar profile
LinkedIn profile
Educational Background:📚
Santiago’s educational journey includes a Doctor of Philosophy (PhD) candidacy in Artificial Intelligence at Pontifícia Universidade Católica do Paraná, where his research encompasses data analytics, problem-solving, and the application of AI in healthcare. He also holds a Master’s Degree in Artificial Intelligence from Universidad Internacional de La Rioja (UNIR), where he focused on data analytics, problem-solving, and research and development with an emphasis on natural language processing and AI model training for language processing. Furthermore, Santiago earned a Master’s Degree in Electronic Systems Engineering from Universidad Politécnica Salesiana and completed a Bachelor’s Degree in Electrical and Electronic Engineering at the same institution, laying the foundation for his career in AI and electronics.
Academia Background
Santiago has a strong background in both academia and industry, having worked in various roles that showcase his versatility and leadership capabilities. Currently serving as an Artificial Intelligence Engineer at Automa Vision since March 2022, he leads the development of computer vision models for smart city applications, focusing on drone imagery for urban feature detection and segmentation. In this role, Santiago collaborates closely with cross-disciplinary teams, provides project leadership, and continuously innovates in AI and computer vision technologies.
Professional Experience:
Prior to his current role, Santiago worked as a Researcher at Universidad Politécnica Salesiana del Ecuador, where he collaborated on developing an intelligent support system for Vitiligo assessment. He also served as the Systems Department Coordinator at Federacion deportiva del Guayas, supporting IT systems, software, and hardware enhancements. Santiago has experience as a Project Engineer at Elsystec S.A., where he was involved in designing, assembling, and commissioning electrical, automation, and field instrumentation projects. Additionally, he worked as a Researcher in Energy Systems at Universidad Politécnica Salesiana del Ecuador, focusing on energy systems research and sustainable energy solutions.
Professional Skills:
Passionate about applying his skills to develop and implement transformative AI architectures, Santiago is committed to aligning these architectures with business goals to foster growth. His diverse experience, coupled with his comprehensive skill set, positions him as a valuable asset in the rapidly evolving field of artificial intelligence and data science.
Research Focus:
Santiago Felipe Luna Romero’s research primarily focuses on advancing energy systems and artificial intelligence. His expertise spans various domains, including anomaly detection in electrical consumption profiles, solar irradiation capture optimization, and innovative applications such as domotics control tools and sign language recognition systems. Santiago’s work integrates computational intelligence, adaptive filtering techniques, and neural networks to enhance signal processing in fields like electromyography (EMG). Furthermore, he contributes significantly to the development of urban digital twins, AI models for inclusivity, and transfer learning models for country border security. Santiago’s multidisciplinary approach highlights his commitment to driving technological innovation across diverse research areas.
Publications (TOP NOTES)
5to. Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad. Memoria académica–Sign language recognition system using MYO ARMBAND and neural network, Cited by 1, Publication date: 2021.
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