Professional with experience in software development, infrastructure automation, and distributed systems. Specialist in microservices architecture, Kubernetes, and DevOps, with expertise in Go, TypeScript, Terraform, and cloud platforms.
As founder of MonDesa, I'm working to revolutionize how we approach disaster prevention and monitoring, leveraging cutting-edge IoT technology and robust software architecture to create more resilient communities.
Full Professor of Computer Science at the Federal University of Fronteira Sul (UFFS), researching computer networks and the Internet of Things. Ph.D. in Computer Science from the University of California Santa Cruz (UCSC), M.Sc. and B.Sc. from UFRGS.
Ph.D. in Electrical Engineering from the University of Southern California (2015), M.Sc. from the University of Nebraska-Lincoln, and B.Sc. from UFC. Researches sensing and wireless communication in lossy materials, focusing on Magnetic Induction-based Underground Sensor Networks (MI-WUSNs), Wake-up on Radio technology, and NIR reflectance spectroscopy.
Designed the first indoor sub-MHz MI-WUSN testbed reported in scientific literature. His findings have applications in precision irrigation, under-debris communication for disasters, pipeline leak detection, infrastructure monitoring, and low-cost remote medical instrumentation.
Full Professor at ICMC/USP and member of the Research for Innovation coordination (CAD-PPI) at FAPESP. Ph.D. in Computer Science from Lancaster University (UK, 2006), with postdoctoral work at the University of Kent and visiting research at the University of Southern California.
Holds six patents, approximately 80 journal articles, and 100 conference papers. His research has been featured in five issues of Revista Pesquisa FAPESP and in media outlets such as Folha de São Paulo and Época Negócios. Main research interests include Internet of Things, Security, and Blockchain.
Computer engineer with experience in embedded systems, distributed architectures, and hardware-software integration. Works on developing a disaster prevention and monitoring platform with IoT, from firmware to device-to-device communication.
His focus is contributing to the embedded system as a whole, ensuring information arrives securely, accurately, and in real time through a robust and scalable software architecture.
Electrical and Electronics Engineering student at USP with technical education in Electronics from CTI UNESP. At MonDesa, manages electronic circuits, performs tests and diagnostics, and programs microcontrollers such as Arduino and ESP32.
Served as Head of Electronics for the EESC USP Baja SAE team, leading PCB design, programming, and system integration with ESP32, applying knowledge in embedded electronics and prototyping.
Student passionate about the intersection of IoT and AI, focused on how connected devices combined with machine learning can drive smarter solutions in environmental monitoring, smart cities, and predictive maintenance.
Currently diving deep into embedded systems, sensor networks, and AI models, building hands-on projects that bring these technologies together to make the world more efficient, adaptive, and resilient.
Student with a strong interest in machine learning, especially training and optimizing deep learning models. Focus on computer vision with PyTorch and TensorFlow.
Experiments with different architectures and training strategies to improve efficiency and accuracy, aiming to work on problems where machine learning isn't just impressive—it's useful.
