Alvaro Maria Diz

Built a production-ready multi-agent AI system enabling natural language data analysis for enterprise users.
• Multi-agent orchestration: Designed stateful workflows using LangGraph, coordinating specialized agents (retrieval, analysis, visualization, planning) for complex reasoning tasks
• Hybrid AI architecture: Implemented SQL + vector search on LanceDB with autonomous Python code generatio

Built a production-ready multi-agent AI system enabling natural language data analysis for enterprise users. Designed stateful workflows using LangGraph and deployed via Docker and Gradio with a ~95% user approval rate.

• Designed and executed Proof of Concept (PoC) projects for Azure AI workloads, transitioning
successful PoCs to production with a focus on Generative AI solutions.
• Developed and deployed multi-agent AI systems using CrewAI, LangChain, Semantic Kernel and Azure AI Services, creating innovative solutions to automate complex decision-making processes and improve business operations. Leveraged als

• Lead an innovative NLP project employing Generative AI and Large Language Models, utilizing cutting-edge technologies like OpenAI API, GPT, Transformers, and Azure to enhance data-driven insights and customer experience.
• Pioneered a machine learning solution for predictive maintenance, utilizing Python, NumPy, and Pandas, achieving improved efficiency and reduced downtime by 30%.
• Facilitated

• Designed and implemented a Generative AI-powered tool for real-time analysis of customer feedback, utilizing Large Language Models and NLP techniques to extract actionable insights from Twitter data, enhancing customer experience and service personalization.
• Mastered the art of fine-tuning BERT models from HuggingFace, achieving human-level accuracy in sentiment analysis and elevating the Voic

Designed and implemented a Generative AI-powered tool for real-time analysis of customer feedback, utilizing Large Language Models and NLP techniques. Fine-tuned BERT models from HuggingFace and boosted TWC Catalyst modeling accuracy by 60%.

• Leading Industry 4.0 projects, putting autonomous manufacturing and digital transformation strategies into practice, using Python and IoT technologies, demonstrating adaptability and expertise in cutting-edge technology.
• Engineered innovative AI-based solutions for internal efficiency, employing Python for predictive maintenance, reducing downtime, and resulting in an annual saving of €20,000

• Finite Element Analysis (FEA) of Polymer Matrix Composites (GFRP, CFRP) with DIGIMAT.
• Analysis of bio-composites behaviour. PLA-Natural Fibres (flax, hemp, sisal)

• Using of LEAN manufacturing tools such as 5S and TPM.
• Obtaining Key Performance Indicators (KPI) and other indicator for preventing risks at the workplace.

1. Data Hacking with Python
2. Machine Learning with Python
3. Data Product Design
4. Deep Learning: Python, Keras, Tensorflow
5. Natural Language Processing (NLP): NLTK, TextBlob, spaCy
6. Machine Learning with Google Cloud Platform
7. Data Hacking with R
8. Big Data with Spark on AWS & GCP
10. Visualization with Tableau
11. Azure ML, DevOps, CI/CD pipelines, Docker.

Master's degree in Data Sciences and Business Intelligence, covering topics such as machine learning, deep learning, NLP, and big data.

• Data processing with Python (pandas, numpy, matplotlib). Using Spyder and Jupyter Notebook, under Anaconda. Introduction to GitHub repositories.
• Statistical analysis and models with R. Exploratory Data Analysis using RStudio.
• Machine Learning with Python and R (Lineal regression, K-Nearest Neighbor, classification trees, Random Forest. Neural Networks and Deep Learning.
• Data mining and NL

Master's degree in Mechatronics and Industry 4.0, integrating mechanical engineering with electronics and intelligent computer control.

Synergistic integration of mechanical engineering with electronics and intelligent computer control in the design and manufacture of industrial equipment and processes.
It is an official master's degree whose curriculum has been verified by the Council of Universities, following a positive report from the National Agency for the Evaluation of Quality and Accreditation (ANECA).

Master of Engineering with specialization in composite materials, including a thesis on finite element modelling of laminate polymeric composite materials.

Specialization in composite materials (ERASMUS). Master’s thesis in Finite Element Modelling of laminate polymeric composite materials.

Master of Engineering in Industrial Engineering, providing advanced knowledge in electronics, automation, mechanics, and business management.

Bachelor of Engineering in Industrial Engineering, covering industrial organization, electrical, mechanical, and chemical engineering topics.

Bootcamps in Business Analytics and Data Science, focusing on data processing, statistical analysis, machine learning, and business intelligence.

Higher education master’s degree. Advanced multipurpose engineering studies applied to the different sectors of the industry.
This master has given me advanced knowledge in disciplines that include Industrial Engineering, such as: electronics and automation, mechanics, electrical installations, industrial chemistry and business management.

Multipurpose studies in Industrial Organization, Electrical Engineering, Mechanical Engineering, Automatic and Industrial Electronics and Industrial Chemistry. Bachelor’s thesis in planning and control of projects using the Odoo ERP and Android devices