Iago Rhudá Ramos
Computer Engineering Student (UTC × PUCPR) · AI & Data Science
Seeking a 6-month end-of-studies internship in Paris starting February 2027.
ABOUT ME
Computer Engineering student specializing in Artificial Intelligence, Machine Learning, and Data Science through a dual-degree between the Université de Technologie de Compiègne (UTC, France) and PUCPR (Brazil).
My focus is building high-reliability intelligent systems where advanced ML models meet strict physical and edge computing constraints. At 18, I founded and ran my own apparel brand, gaining hands-on discipline in inventory management, supplier negotiations, unit economics, and operational resource allocation. At Packform and Irrigate, I turned this practical mindset into robust engineering: automating complex enterprise workflows in Python and developing C/C++ firmware on ESP32 microcontrollers for high-reliability embedded systems and end-to-end automation.
Interests
EXPERIENCE
Track record in enterprise workflow automation, embedded edge firmware, and computer engineering.
Automation Engineer Intern
Curitiba, Brazil
- Automated end-to-end enterprise workflows and data pipelines using Python and RESTful API integrations.
- Modeled and orchestrated business-critical BPMN processes on Zeev, removing communication bottlenecks across operational departments.
- Streamlined operational handoffs across business units, accelerating workflow throughput and end-to-end process visibility.
Embedded Systems Developer Intern
Curitiba, Brazil
- Developed modular C/C++ firmware for ESP32 microcontrollers deployed in real-time agricultural telemetry nodes.
- Implemented low-power wireless IoT communication protocols for soil sensing and automated irrigation actuators.
- Engineered fail-safe sensor telemetry routines and low-latency wireless packet transmission for outdoor field deployments.
Teaching Assistant (Monitoria Acadêmica)
Curitiba, Brazil
- Mentored undergraduate engineering students in programming fundamentals, algorithms, and data structures.
- Mentored undergraduate engineering students through weekly programming labs, algorithm design, and structured debugging.
EDUCATION
Université de Technologie de Compiègne (UTC)
Double Degree - Ingénieur en génie informatique spécialisé en IA
Compiègne, France
Pontifícia Universidade Católica do Paraná (PUCPR)
Bachelor's Degree - Computer Engineer
Curitiba, Brazil
CEEP Curitiba
Building Technician
Curitiba, Brazil
SKILLS
Structured breakdown of core engineering capabilities, frameworks, and applied tools.
ML & Tabular Data
Predictive modeling, tabular foundation models, and statistical data engineering.
Generative AI & RAG
Knowledge retrieval architectures, vector embeddings, and LLM applications.
Embedded Systems & IoT
Edge computing, microcontrollers, sensor telemetry, and hardware-software interfacing.
Automation & Backend
Python API integrations, asynchronous automation, and Zeev (BPMN) process orchestration.
Systems & Tooling
Linux environments, version control, containerization, and data persistence.
Natural Languages
Professional working proficiencies in multilingual technical environments.
Featured Engineering Projects
A curated showcase of artificial intelligence, software architecture, and embedded systems engineered for performance, precision, and scalability.
Natural Language Search Engine
NLP-powered search and information retrieval engine built from scratch in Python, featuring a Glassmorphism web dashboard, TF-IDF ranking, spell-checker, and boolean filters.
Hybrid Collaborator Recommender (RAG + Knowledge Graph)
Hybrid recommendation engine matching UTC researchers by expertise, combining Retrieval-Augmented Generation with a knowledge graph.
Quadrotor Dynamics & Intelligent Flight Control (PIBIC)
Mathematical dynamics simulation, state-space modeling, and intelligent trajectory stabilization for unmanned aerial vehicles (UAVs).
Portfolio Site v2
High-performance personal web platform engineered with Angular SSR/Prerender, 3-language i18n, and an Apple-inspired minimalist design system.
PUBLICATIONS
Peer-reviewed research and academic publications advancing Artificial Intelligence for structural health monitoring and industrial reliability.
Tabular Prior-Data Fitted Network for Structural Damage Prediction
Peer-reviewed paper accepted at COBEM 2025. Evaluates TabPFN for structural health monitoring (SHM), achieving 99.18% accuracy without hyperparameter tuning.
Wind Turbine Blade Crack Detection via PCA & Logistic Regression
PUCPR undergraduate research supervised by Prof. Dr. Helon Vicente Hultmann Ayala, achieving 92% predictive accuracy on wind turbine blade structural cracks.
CONTACT
Currently open to discussion for a 6-month end-of-studies internship in Paris starting February 2027.
LinkedIn:
Connect on LinkedIn for professional updates, technical discussions, and career networking.
GitHub:
Explore my open-source codebases, Machine Learning implementations, and systems architecture on GitHub.
Lattes CNPq:
Official CNPq Curriculo Lattes (Brazilian Academic Research Registry).