Young researchers were awarded at the MEDAL final conference

From 8–10 October 2025, the final conference of MEDAL (Methodological Excellence in Data-Driven Approaches to Linguistics) took place. At the end of the conference, the best young researchers were announced. Top three places were awarded, with the third place shared between two participants. The young researchers shared what their studies focus on and what the experience meant to them.

1st place: Loïs Dona (Max Planck Institute for Psycholinguistics)

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My research explores how facial signals contribute to the emergence of communication systems. Facial signals can provide rich pragmatic information, which may influence how people coordinate and communicate when building these new communication systems.

Receiving this recognition reaffirms that the topic I am exploring resonates beyond my immediate research community. It motivates me to continue pursuing and refining these novel ideas and approaches to these research questions.

The MEDAL experience has been incredibly inspiring. It offered valuable opportunities to exchange ideas with talented peers and experts from diverse disciplines, connect with research beyond the immediate scope of my field, and spark new directions for my own work.

2nd place: Hasan Dikyuva (Max Planck Institute for Psycholinguistics)

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My research focuses on negation in Turkish Sign Language (TİD). Using corpus-based analysis, I explore how Deaf signers express negation through both manual and nonmanual markers. The study provides new insights into how negation operates in sign languages and contributes to a deeper understanding of TİD’s structure and typology.

This recognition is very meaningful for me as a Deaf researcher. It values not only my academic work but also the visibility and representation of Deaf scholars in linguistic research. It encourages me to continue investigating sign languages from both linguistic and community-based perspectives.

The MEDAL experience has been transformative. I have learned advanced methodological and experimental approaches that allow me to study sign language structure more systematically and deeply. These new skills and perspectives have inspired me to refine my research questions and to approach sign language data with greater precision and creativity.

3rd place: Magda Matetovici (Max Planck Institute for Psycholinguistics) and Annika Kängsepp (University of Tartu)

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Magda Matetovici

My research focuses on the role of parents and the language opportunities they create in explaining individual differences in language development. At the MEDAL conference, I presented preliminary results on the similarity in language skills between the members of the nuclear family and how this might relate to what we think matters in first language acquisition (based on our ongoing systematic review).

I am grateful for the positive feedback and excitement with which our research was met. Through MEDAL I could meet language scientists with very diverse interests and backgrounds, which pushed me to see connections between our research and broader questions about language. As an early career researcher, I felt a strong sense of support and community.

Annika Kängsepp

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My research focuses on the variation in the case forms of Estonian indefinite pronouns. In this presentation, I used keegi 'someone' as an example to show how language variation can be studied using multi-method approach that combines corpus studies and eye-tracking.

It's a great honour for me to receive such recognition, especially since it's the first time my research has been acknowledged at a conference. It really encourages me to continue working on my topic.

Over the last three years, MEDAL has provided methodological support throughout my doctoral studies, offering workshops, masterclasses, and summer schools, that have equipped me with essential knowledge and skills which I have been able to apply directly to my research.

Events are organised by the Methodological Excellence in Data-Driven Approaches to Linguistics (MEDAL) consortium and are financed by the EU Horizon Europe programme (101079429) and UK Research and Innovation organisation (101079429).

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