Eduardo is Professor for Intelligent and Adaptive User Interfaces with the Institute of Interactive Systems and Data Science, Graz University of Technology (ISDS TUGraz) and he is also Research Manager of the Knowledge Visualisation group at Know-Center GmbH. His interests lie in the field of intelligent interactive systems, in particular studying human aware computing and cognitive aspects of data analytics, virtual and augmented reality interfaces. Eduardo obtained his PhD in Computer Science from Graz University of Technology, his Msc in Information Science and Technology from Osaka University, and holds a degree in Software Engineering from National University of Technology, Argentina. .


The user interface encompasses a range of actions and feedback that enable the exchange of information between human and computer. My research is directed towards investigating and develooping computational artefacts that adapt to the human potential, investigating how the interaction unfolds, and proposing methods to apply machine intelligence to improve on the human-machine task. I am the director of the Human Computer Interaction Center, and the head of the Intelligent User Interfaces Group at Graz University of Technology.

The Human Computer Interaction Center is a joint effort of various institutes developing technologies for human machine interaction. It offers the facilities and expertise to develop and study a broad range of state-of-the-art technologies aiming at extending human capacities (to deal) with technology.
The Intelligent User Interfaces Group performs research at the frontier of artificial intelligence, data science and human-machine interaction with the mission to create interfaces that exploit the synergies between humans and computing systems.

Selected Publications

Granit Luzhnica and Eduardo Veas. 2019. Optimising Encoding for Vibrotactile Skin Reading. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI '19). Association for Computing Machinery, New York, NY, USA, Paper 235, 1–14.
Cecilia di Sciascio, Peter Brusilovsky, and Eduardo Veas. 2018. A Study on User-Controllable Social Exploratory Search. In 23rd International Conference on Intelligent User Interfaces (IUI '18). Association for Computing Machinery, New York, NY, USA, 353–364.


I celebrate diversity and enjoy working in an environment of openess that avails freedom to exchange opinions, tolerance and respect. I am proud to advise a diverse group of motivated researchers.

    Research Group
  • Lucas Iacono (Post Doc),
  • Granit Luzhnica (Post Doc)
  • Adrian Remonda (PhD Candidate)
  • Jeremy Chan (PhD Candidate)
  • Joerg Simon (PhD Candidate)
  • Reihaneh Manteghi (PhD Candidate)
  • Benedikt Tschechner (Msc Student)
  • Aleksandra Krajnc (Msc)
  • Oliver Prentner (Senior Engineer)
  • Cecilia di Sciascio (PhD)
  • Belgin Mutlu (PhD)
  • Ilija Simic (Msc)
  • Fiona Draxler (Msc)
  • Lukas Rath (Msc)
  • David Strohmeier (Msc)


I have put together a curriculum for modern human computer interaction topics complementing the offer in visual computing at TUG. It consits of four courses offering students to learn concepts in contemporary computer science and human computer interaction while building and evaluating prototypes. The final phase will be in place with the class on Wearable Computing in SS2021.

User Interfaces: This course looks into building interfaces for human machine interaction from the electronics, hardware and software using fast prototyping techniques. Students learn about human perceptual and motor capabilities, user input / output devices to extend the human capacity. They build a hardware prototype, code a driver and demo application.

Evaluation Methodology: The course introduces scientific methods applied in human computer interaction. The student will learn how formulate research questions and hypotheses, how build evaluations to test those hypotheses, how to record and collect evidence, analyze it, derive knowledge from it, and report findings from evaluations.

Intelligent User Interfaces: The course introduces important concepts inherent to intelligent systems that interact with humans. Students learn to design data collection strategy within the interface, use machine intelligence to learn some aspect of human behavior, and use the model in the interaction.

Wearable Computing: this course introduces the skills needed to design hardware, software and a shell for wearable products. The course offers the opportunity to study topics of data acquisition in wearable devices and to dive in topics of machine intelligence to develop user models based on wearable sensor data.

By Eduardo Veas.