Grants from Matti Lehti fund for the year 2024 awarded
Timo Korkeamäki, The Dean of the School of Business, has made a decision on Matti Lehti grants for the year 2024.
The Matti Lehti fund has been donated to develop and encourage research, teaching and studies on digital information society in the School of Business. The School of Business is co-funding part of the grants.
Grants are given to:
Doctoral researcher Jiancio Liao for research expenses on a study titled “Effects of Generative Artificial Intelligence Identity Disclosure on Consumer Behavior: Mechanisms and Response Strategies”, 3000 €
Professors Eeva Vilkkumaa and Pekka Malo for research expenses on a study titled “What kinds of heuristics do people use when making multiattribute choices?”, 6000 €
Professor Matti Rossi for expenses on conducting an “Experiment with Generative Adversarial Neural Networks on the Digital Platform”, 6000 €
Professor Yong Liu for research and travel expenses related to a study titled “Embracing the Future: Service Robots for Business Values and Social Welfare”, 6000 €
Doctoral researcher Sidhant Ritwick for travel expenses related to a study titled “Physicians versus Google Doctors: The Evolution of the Relationship Between Experts and Laypersons Through Digital Tools”, 3000 €
Doctoral researcher Ksenia Lashkova for travel expenses related to a study titled “Customer engagement in gamified digital branded environments: insights for AI-based personalization”, 1500 €
The total sum of all the grants is 25500 euros.
Call for Matti Lehti grant proposals 2024
The applications must relate to the theme of digital information society
Read more news
ACRIS service restored
The ACRIS research information management system is now open following the planned service break on 13–20 April 2026.
Science must have a voice in society – but how?
Trust in science has fallen in Finland by almost ten percentage points in two years
Meet our startup: Proteins.1 aims for a breakthrough in early disease detection
Biotechnology startup Proteins.1 is developing a technology that could enable the detection of diseases such as cancer months, or even years, earlier than is currently possible. The key lies in identifying individual proteins from a blood sample.