Data scientists and psychologists are trained in complementary domains, making their collaboration increasingly vital for problems that demand both analytical rigor and deep behavioral insight, ultimately advancing human understanding and decision-making.

This interactive 90-minute workshop aims to bridge disciplinary gaps and encourage collaborative problem-solving. By integrating perspectives from both domains, we seek to generate innovative approaches that benefit both fields and in extension society. Participants will engage in group activities, and panel discussions designed to build mutual understanding and explore practical strategies for effective interdisciplinary collaboration.

The goal of this session is to create a resource guide with key readings, tools, and contact networks to support ongoing interdisciplinary work.
 

Program

The session will be structured as follows:
 
Introduction & Icebreaker (10 minutes)

• Overview of workshop goals and importance of interdisciplinary collaboration.
• Gathering expertise and perspectives from participants.

Presentations and panel discussion: Overcoming the knowledge gap (30 minutes)

• Short presentations: Focus on case studies of successful psychologist-data scientist collaborations
• Panel discussion: Experts from both fields share insights on navigating interdisciplinary challenges

Breakout session: Tackling real-world problems (15 minutes)

• Participants divided into mixed teams to discuss challenges at the intersection of psychology and data science (e.g., mental health applications, behavioral data analysis, ethical AI in psychology)
• Each group develops actionable solutions and collaboration strategies.

Presentation & open discussion (20 minutes)

• Groups share key takeaways and proposed strategies with the larger audience.
• Open discussion on implementing collaboration strategies in practice.
   

Closing & next steps (5 minutes)

• Summary of key insights
• Sharing resources and opportunities for continued collaboration.
• Encouragement to join interdisciplinary networks and research initiatives.
   

Speakers’ list

• Andreas Elleby Jespersen, PhD student, Institut for Psykologi, University of Copenhagen
• David-Levente Kovacs, PhD student, IT University of Copenhagen (ITU)
• Nicole N. Lønfeldt, Associate Professor, Region Hovedstadens Psykiatri
   

Level

Intermediate: Suitable for attendees with basic understanding or experience in psychology or data science who want to enhance interdisciplinary collaboration skills.

Organisers

• Stella Graßhof, Assistant Professor in the Data Science section at the IT University of Copenhagen, and the Pioneer Centre for AI.
• Line Clemmensen, Professor at The University of Copenhagen.
• Benjamin Arnfred, postdoctoral Researcher and clinical psychologist at VIRTU, Copenhagen Research Center for Mental Health.
• Sneha Das, Assistant Professor in the department of applied mathematics and computer science at the Technical University of Denmark.
• Dan Witzner Hansen, Professor at IT University of Copenhagen. Co-lead of the Extended Reality Collaboratory in the Danish Pioneer Centre for AI.
• Christian Hardmeier, Associate Professor at the IT University of Copenhagen. Co-lead of the Speech and Language collaboratory in the Danish Pioneer Centre for AI.