Experience and Projects Done

I hope that my readers here, are also creating amazing solutions with Artificial Intelligence!

Here you will find:

Work Done

Some links and videos showing my professional portfolio.

Federated Data Pipeline

Utrecht University - Project Homepage

As Core Scientific Lead, I designed and delivered this international project done by Utrecht University involving multiple European universities to evaluate the effectiveness of heterologous and booster COVID-19 vaccination schedules in five countries. Our research used a cohort approach, focusing on both children and adults who completed a full primary vaccination regimen.

I led the development of a robust federated data pipeline, ensuring data from all partners adhered to a common data model and harmonized semantic concept libraries. This enabled consistent analysis and interpretation of health data across diverse international contexts protecting privacy of the participants as well.

• Utrecht University, The Netherlands (Consortium Lead)
• UMC Utrecht, The Netherlands
• VAC4EU, Belgium
• Democritus University of Thrace, Greece
• APHP, France
• ARS, Italy
• INSPIRE, Italy
• SoSeTe-Pedianet, Italy
• Rīga Stradiņš University, Latvia
• PHARMO Institute, The Netherlands
• RIVM, The Netherlands
• IACS, Spain
• IDIAPJGol, Spain
• RTI Health Solutions, Spain
• Servicio Navarro de Salud, Spain
• Teamit Institute, Spain
• DSRU, UK
• AEMPS, Spain (Coordinator)

• Study Protocol (approved by the European Union)
• CoVE Project Repository (Zenodo)

• Effectiveness of homologous/heterologous booster COVID-19 vaccination schedules against severe illness in general population and clinical subgroups in three European countries (PubMed)

Workload AI Classification

Read the full article

As lead data scientist and co-author, I contributed to a peer-reviewed study published on the use of artificial intelligence to develop a classification system for nursing workload in hospital settings. The research demonstrates how AI and data-driven approaches can support healthcare resource management and improve patient care.

• Title: "Nursing workload: use of artificial intelligence to develop a classification system for hospital settings"
• Application of AI in healthcare operations
• Nursing workload measurement and classification
• Data-driven decision support for hospital management
• Collaboration between clinical and data science teams

Covid-19 Scenarios (by Neherlab)

My contribution to the model, was to implement a new flux in the SIR model called “Palliative Flux”. Coding with Typescript, Python and Node.js and involving many kinds of data validations and complex epidemiology modelling.

To accomplish this, I had to set cloud environments (dev and production) with Continuous Integration and Delivery of software, so statisticians could work on local models.

Our environment was equipped with a data parser, to capture data from our local government dashboards and after processing than, I have customized the calculator to build specific scenarios for 26 local regions.

This was a work group with collaboration from statistics, medicine and computer science teachers from the federal university along with state authorities.

References: https://www.covid19-scenarios.org

AGHUse (by Hospital de Clínicas de Porto Alegre)

Co-author of the registered GPL software at INPI, AGHUse is a comprehensive EHR (Electronic Health Record) and ERP (Enterprise Resource Planning) system designed for healthcare providers of all types.

I initiated the project as it's main coordinator in charge for all developers, and named it AGHUse together with the communications team, after the original AGHU "mother" project and the old AGH "father" project. As the original Technical Leader and later IT Executive, I led the rollout in a large 1,000-bed hospital, covering primary care, emergency, maternity, psychiatry, heart transplants, and all the advanced features needed for such a complex environment.

From the beginning, I have witnessed the project's growth and its positive impact across Brazil. By 2016, AGHUse became the most widely adopted university hospital software in the country. In 2017, it received the Public Innovation Award from ENAP.

Today, the project is maintained by the "Comunidade AGHUse," which includes partners such as UNICAMP, the Army, Air Force, local governments, and other universities.

Hospital de Clínicas de Porto Alegre (+900 beds) was appointed by the federal government in 2009 as a blueprint for a digital healthcare business model. Now its software is shared across the country.

References: https://www.hcpa.edu.br

AGHU (by EBSERH - Empresa Brasileira de Servicos Hospitalares)

AGHU is a complete EHR (Electronic Health Record) designed to fit University Hospitals in all 5 regions from Brazil.

From South to North, I was the former Technical Leader, co-authored the source code in Java and later became the IT Executive in charge for rolling out it on the first 23 hospitals, including small, medium and large hospitals.

Now the project is maintained by EBSERH in partnership with a community formed by multiple universities.

Instructor: Cláudia Lemos Nascimento - Nurse
Publication Date: 2024-03-11
References:

Infection Surveillance Assistant (by Qualis Infectologia)

As head of AI and data expert, I've built the AI model to implement ISA - Infection Surveillance Assistant. Made by automated artificial intelligence running at Amazon AWS. Provides solutions for hospitals to revamp infection control.

In the future, we hope ISA will be an expert in infection related problems.

References: https://www.portalqualis.com.br

My corporate experience

• KHC – Amsterdam Center of Excellence: Working on global projects unifying AI and data governance using advanced Stewardship and Data Quality tools. Collaborating with multidisciplinary teams in the US, Europe and Asia in a leading Forbes 500 company.
• Hospital de Clínicas de Porto Alegre: Led digital transformation and large-scale healthcare IT projects at one of Brazil’s premier university hospitals, focusing on EHR implementation, data governance, and operational excellence.
• Bunge Ltd.: Gained valuable experience in the agribusiness sector, working on technology solutions that supported logistics, supply chain, and business operations for a global food company.
• Claro Telecom S.A.: Developed and maintained telecom systems, contributing to the growth and modernization of one of Brazil’s largest telecommunications providers.
• Petróleo Ipiranga S.A.: Early career experience in the energy sector, supporting IT infrastructure and business processes for a major petroleum company.

Experience with:

1. Unified AI and Data Governance;
2. AI Product Design and Development;
3. Software delivery, maintenance, and development;
4. Enterprise change management;
5. Leadership of technical teams and C level advisory;
6. Negotiation with customers and suppliers;
7. International partnerships;
8. Consulting;
9. Strategic Planning;
10. Entrepreneurship;

List of skills

My know-how using information technology, including languages and tools that I am using now.

Tech Skills

1. Data Governance and Data Quality;
2. Artificial Intelligence (from theory to product delivery);
3. Machine Learning with Python (understanding the caveats);
4. Data Science engineering (ETL and large data manipulation basics);
5. AWS and Google Cloud administration (to save money and stay safe);
6. PostgreSQL and MongoDB basic administration (20 years working with databases);
7. Software Development with TypeScript and Node.js (I am updated with new languages skills);
8. Epidemiology and statistics literacy (to talk with scientists and experts);
9. Agile, DevOps, containers and cloud automation (to develop adding value);

Other Information

If you need additional information about accomplishments from my resume, we can have a coffee and have a nice talk by DM on Twitter: @tiagoandresvaz