Gabriel Campanelli Iamato

Undergraduate student in Data Science at the Institute of Mathematics and Computer Sciences of the University of São Paulo (ICMC-USP) and Informatics Technician from the Technical Industrial School "Prof. Isaac Portal Roldán" UNESP.Currently works as a Scientific Initiation researcher with a PIBIC/CNPq scholarship at the Institute of Mathematics and Statistics of USP (IME-USP). In a project linked to the National Institute of Science and Technology for the Future Internet (InterSCity) and BikeScience, he develops algorithms to support the expansion of bike-sharing systems.Previously, he was a PIBIC Jr. (CNPq) researcher at the Faculty of Sciences at UNESP, also in collaboration with the BikeScience project. His research involved statistical analysis of the Bike Itaú system in São Paulo, including interactive visualizations and proposals for system expansion based on the spatial distribution of trips per station and infrastructural factors in the city. For this work, he received an Honorable Mention in the international phase of SIICUSP (International Symposium on Scientific and Technological Initiation at USP) and presented his findings at the XXXVI Scientific Initiation Congress at UNESP. The relevance of the project led to his selection to represent Brazil at the Project Presentation Day at University College Groningen (UCG), in the Netherlands.He is also part of the Artificial Intelligence Advancement Network (RAIA) as a software developer, where he applies techniques in computer vision, convolutional neural networks (CNNs), fine-tuning, and object detection using TensorFlow, PyTorch, Keras, and MediaPipe. One of the projects he contributed to aims to democratize access to sign language, promoting the inclusion of deaf individuals through AI-based solutions.At the ICMC Jr. student-run consulting company, he worked as a data science consultant and sales advisor. He led projects such as the identification of trending music patterns on Spotify and conducted statistical and geospatial analyses on biological data related to the appearance of marine animals, among others.As a teaching instructor in the DATA extension group, he has strong technical proficiency in Python and its main data science libraries (pandas, scikit-learn, matplotlib, seaborn, geopandas, PyTorch, TensorFlow, among others), as well as experience with C, C++, C#, SQL, JavaScript, PHP, Arduino, Flask, Laravel, and Git version control. He has advanced English skills and international experience presenting academic projects. (Source: Lattes Curriculum)