Lucas Iacono PhD.

About me…

I am a researcher and educator working on the design, management, and governance of data-intensive computational systems, with a focus on how data practices shape the trustworthiness, sustainability, and societal impact of artificial intelligence.

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My academic career spans more than a decade of university teaching and research in Argentina, followed by senior research, leadership, and teaching roles in Austria. I combine a strong background in engineering and computer science with long-term experience in building and governing data infrastructures that support reliable, transparent, and responsible AI systems.

Research Focus

My research focuses on data management as a foundational pillar of trustworthy artificial intelligence. I study how data acquisition, integration, curation, governance, sharing, and processing mechanisms directly affect the reliability, transparency, robustness, and sustainability of AI systems.
Rather than treating trustworthiness as a purely algorithmic problem, my work approaches AI systems as data-driven sociotechnical systems, embedded in institutional, regulatory, environmental, and domain-specific contexts.

Key Research Areas

Data Management for Trustworthy AI.
- Data-foundations of trustworthy AI, including data quality, provenance, interoperability, sovereign data processing, and energy and cost-efficient data pipelines.
Data Infrastructures, Data Spaces, and Governance.
- Design and analysis of data spaces and large-scale data infrastructures as organizational and institutional frameworks enabling trustworthy data sharing and processing for AI across industry, the public sector, and sustainability-oriented domains.
Data-Driven Sustainability and Environmental Monitoring.
- Use of sensor networks, machine learning, and cloud-based data management to support environmental monitoring and risk mitigation. This includes long-term research on frost prediction in agriculture, combining sensor networks, data pipelines, and machine learning models to support decision-making in climate-sensitive rural contexts.
Data Management Systems for Multi-agent Systems.
- Data sharing and processing pipelines for multi-agent systems with a focus on decision-making in data-intensive environments.

Current Positions

Research Area Manager – Know Center Research GmbH
Area Data Management for Artificial Intelligence
University Lecturer – Institute of Human Centric AI – Graz University of Technology
Responsible for the following courses:
- Data management – Summer Semester
- Databases – Winter Semester
- Data Integration and Large-scale Analysis – Winter Semester
Supervisor of bachelor’s and master’s theses – Institute of Human Centric AI – Graz University of Technology

Academic Trajectory and Societal Engagement

Before my current roles in Austria, I spent more than ten years as a university professor and researcher in Argentina, where my work combined academic research on data-intensive systems with strong societal engagement.

In parallel to my research, I designed and led educational initiatives promoting STEAM education in rural and socioeconomically vulnerable contexts. This work included (i) seminars on sensor development based on open-source software and hardware technologies for frost prediction in rural schools, (ii) robotics workshops in schools facing conditions of poverty, and (iii) robotic competitions for students of universities, secondary and primary schools.

These experiences shape my academic perspective on data, AI, and technology as game-changers for overcoming societal issues.

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