My interest in Machine Learning began in high school, when I started exploring Python, statistics, and data analysis. This led me to earn the IBM Professional Data Science Certification in 2023. I am currently pursuing a B.Sc. in Computer Science at PUCPR. From 2024 to 2025, I conducted undergraduate research on unsupervised representation learning with Autoencoders, improving cross-domain generalization for kidney stone detection in medical imaging. Currently, my research focuses on Vision Transformers for digital pathology, especially tumor and leprosy classification in histopathology images. I am also co-author of an international paper presented at IEEE SMC 2025 on federated learning for kidney stone detection, and was Technical Lead of the winning team at Renault Transformation Day.

I am interested in connecting with professionals in industrial, financial, and legal sectors to better understand operational challenges and identify opportunities for ML-driven automation. In Brazil, these areas still rely heavily on manual processes, creating strong potential for data-driven solutions. I am also interested in learning how to optimize complex ML models and architectures to run efficiently on IoT and embedded devices with minimal computational resources.

I work on applied and research-driven ML systems across industrial and medical domains, specializing in Computer Vision. My work includes predictive maintenance models for 3-phase motors using electrical current analysis and harmonic decomposition. In research, I previously optimized Autoencoder based models for cross-domain medical imaging tasks. Currently, I investigate Vision Transformers for digital pathology and histopathological image analysis.

I was born in Paraná, Brazil, but spent most of my life in Rondônia. Passionate about science and technology, I decided in high school to pursue Computer Science and moved away from my family to study at PUCPR. During my studies, I developed a strong interest in Artificial Intelligence and Machine Learning, working on research projects as a PIBIC scholar, participating in programming competitions with PUCPR’s women’s team, and contributing to university technology initiatives. I am currently pursuing my master’s alongside my undergraduate degree through the PIBIC Master program with a full scholarship.

Machine Learning and Artificial Intelligence in general, including deep learning, data-driven systems, and model interpretability. I’m interested in solving complex problems using technology and collaborating on innovative projects that apply ML to real-world challenges. I enjoy both research-oriented work and hands-on development, especially in environments that encourage experimentation and creative problem solving.

I’m currently pursuing a master’s degree alongside my undergraduate studies through the PIBIC Master program at PUCPR. My research explores how SHAP-based Explainable AI can be integrated with Symbolic AI to make deep learning models more interpretable, particularly for medical applications.

I am a Computer Science senior currently working as a QA professional in the Artificial Intelligence team at Vivo. I have experience with model evaluation, LLMs, RAG systems, and prompt engineering, and I conduct research in neural networks focused on uncertainty and evaluation metrics. I am passionate about applying generative AI to real-world problems, combining analytical thinking, quality assurance, and engineering to build robust and reliable intelligent systems.

I am particularly interested in generative AI, LLM applications, RAG systems, and multi-agent architectures. I’m looking to deepen my knowledge in AI evaluation, model reliability, and scalable AI systems in production. I’m also interested in collaborating on real-world AI products that combine research, engineering, and quality to build robust and trustworthy intelligent solutions.

I am currently conducting research in neural networks, focusing on uncertainty estimation and model evaluation. My work explores techniques such as Monte Carlo Dropout to improve reliability and robustness in AI systems.

Hello! It's a pleasure to meet you, I'm Graziela, and I'm very happy for the opportunity to share a little about myself. I'm 20 years old, a Marketing student, and I work in the field, which is, incidentally, my great passion. Throughout my professional career, I've worked as a coordinator in a startup, where I had the opportunity to learn about and work with different aspects of marketing. Currently, I'm an intern at a multinational company, balancing this experience with my studies and also with projects as a social media manager. In addition, I actively participate in academic projects and lectures, always seeking to develop my skills and grow professionally.

Developer marketing, growth and performance marketing, paid traffic, SEO, social media strategy, branding, marketing analytics, customer success, design partners, speaking opportunities.

Currently, I am a Marketing student and work in the field at a multinational company in the paper and pulp sector. In parallel, I am the founder of a social media company, where I strategically help early-stage businesses build their presence, position themselves on social networks, create a community, and acquire new customers.