Personal profile

Academic background

Tilman is an Associate Professor with the Knowledge and Intelligence Design (KInD) section in the Department of Sustainable Design Engineering (SDE) of the Faculty of Industrial Design Engineering (IDE);

He holds a diploma in Media Computer Science from the Ludwig-Maximilians University in Munich (Germany), an Honours Degree in Technology Management from the University of Munich, a Master of Science degree in Web Science from the University of San Francisco (USA), and a PhD in Computer Science from the University of Stuttgart (Germany).
He is an expert in the design and implementation of technologies that measure and adapt to cognitive abilities, thereby supporting memory and information processing. 

Before joining TU Delft, he was a Senior Lecturer at the University of Melbourne, worked as a Project Assistant Professor at Osaka Prefecture University in Japan and was a visiting researcher at the MIT Media Lab. 

Tilman is a Fulbright scholar and received the Wolfgang Heilmann Award twice for Humane Usage of Information Technology and Education for the E-Society. He procured competitive funding both internationally and domestically, including from the NHMRC and collaboration grants from the Japan Science and Technology Agency.

He is an Associate Editor for the PACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) journal and serves as an Associate Chair for CHI and other leading conferences in the field of human-computer interaction. He is a co-founder of the SIGCHI Melbourne Local Chapter.

Research profile

Tilman builds and investigates technologies that enhance people’s cognitive abilities to help them navigate a world full of information and distractions through pervasive and ambient computing. He applies user-centered design principles to design, implement, and deploy ubiquitous computing systems, specifically in the following application areas:

1. Cognition-Aware Systems

Cognition-aware systems are technologies that sense users’ cognitive states, model systematic variations, and adaptate their interface and behaviour. Using biophysical sensors and interaction data, this work focuses on quantifying and modelling users’ attention, alertness, and general cognitive performance. By considering the cognitive state as a context variable, we can build better reading interfaces and learning systems while preventing information overload. In recent years, however, it has become clear that optimising the information bandwidth between human and computer is also about assuring the quality of information processing. Together with behavioural psychologists and the information retrieval community, this work has pioneered a series of workshops at CHI about technology design that supports critical thinking and the role that cognitive biases play in system interactions and information consumption. The resulting bias-aware systems are capable of detecting and helping to mitigate the effects of cognitive biases in opinion formation and decision-making.

2. Intelligent Reading Interfaces

Reading takes increasingly place on digital devices where medium, interface, and content presentation are highly dynamic. Additionally, the information age provides us with the challenges of information overload leading to the creation of new reading behaviours. This work strand investigates these behaviours and designs interfaces with the goal of providing better readability and instilling better reading habits in users. 

3. Digital Health

Technological developments in ubiquitous sensing, data source integration, and machine learning offer new opportunities for patient care. Technologies provide the means to continuously measure individuals’ behaviours and health states to support the achievement of behavioural goals. This research strand focuses on the development of monitoring technologies and conversational interfaces that help instil and sustain healthy behaviours. Novel sensors are developed using thermal cameras to monitor hand hygiene quality and near-infrared spectroscopy to detect pill and infusion content. By devising a trigger mechanism using inaudible audio to trigger Google Home apps, the off-the-shelf voice assistant becomes proactive. Additional sensors are used to detect opportune moments to engage patients in their homes based on their proximity, vitals, and privacy settings and are used to collect patients’ self-assessments throughout the day. Smart monitoring paired with a direct intervention line to caretakers can help patients manage their chronic diseases and keep them out of the hospital longer.


Education/Academic qualification

Doctorate, Cognition-aware Systems to Support Information Intake and Learning, University of Stuttgart

Award Date: 2 Dec 2016

Master's degree, Web Science, University of San Francisco

Award Date: 31 Dec 2011

Honors Degree in Technology Management, Technische Universität München

Award Date: 15 Nov 2010

Diploma in Media Computer Science, Ludwig Maximilians University

Award Date: 18 Oct 2010

External positions

Honourary Senior Research Fellow at The University of Melbourne

10 Sept 20239 Sept 2028


  • QA75 Electronic computers. Computer science
  • human-computer interaction
  • ubiquitous computing


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