András Lőrincz

Also known as András Lörincz

András Lőrincz is an ELTE AI researcher whose work connects machine learning with human-machine collaboration and medical applications. He trained in physics and turned toward AI after experiments in Chicago showed that systems could learn from data. His work has included medical cyber-physical projects, a 2016 paper on combining deep and knowledge-based systems, and a deep-learning method for facial-expression recognition and gaze monitoring. As of October 2026, he is the founder of ELTE's Neural Information Processing Group and organizes a workshop on precision psychiatry, multimodal clinical AI, and human-AI interaction.

Now at: Department of Artificial Intelligence, Eötvös Loránd University and Eötvös Loránd University
Works: 338
Citations: 3,174
h-index: 29
Badges: Bridge
Wayfarer
Loyal

Publication numbers from OpenAlex, as of 18 October 2026.

Timeline

1975–1997

A path from physics to AI

He earns a physics degree from ELTE in 1975 and a university doctorate there in 1978. From 1975 to 1997, he works at the Hungarian Academy of Sciences' Institute for Isotope Research; his research appointments include the University of North Carolina in 1980–1981, the University of Chicago in 1982–1984, Illinois Institute of Technology in 1988–1989, and Brown University in 1991. In Chicago in 1982–1984, he sees that AI learning from experiments can be faster and more accurate than modeling calculations.
1997–1998

Mindmaker and ELTE

In 1997–1998, he serves as scientific director of Mindmaker Kft.; in 1998, he joins ELTE's Faculty of Informatics as a researcher.
2004–2006

A prize and a fellowship

In 2004, he receives the Kalmár Prize from the John von Neumann Computer Society. The European Coordinating Committee for Artificial Intelligence elects him a Fellow in 2006.
Since 2006

Digital finance and smart factories

His funded project topics from 2006 include digital finance, smart factories, medical cyber-physical systems, and cooperation among distributed intelligent agents.
2016

Cognitive Deep Machine

In a 2016 paper, he and five coauthors describe how deep components can combine with facts and confirmation rules in knowledge-based systems. They demonstrate the approach on the State Farm Distracted Driver Detection benchmark.
2019–2020

Deep learning for interaction

In 2019, ELTE names him Innovative Researcher for a deep-learning method that uses facial-expression recognition and gaze monitoring in human-computer interaction. He receives ELTE's Eötvös gyűrű in 2020.
As of October 2026

Founding ELTE's NIPG

As of October 2026, he is the founder of ELTE's Neural Information Processing Group in the Department of Artificial Intelligence. In October 2026, he organizes a workshop on precision psychiatry and multimodal clinical AI.