Data Science for Mental Health (DS4MH) @ The Alan Turing Institute
About Us
The vision for this interest group is to kick-start one or more projects using contemporary data science and multi-modal data for mental health to provide insight and benefit for individuals, clinicians, and contribute to fundamental research in mental health (including dementia) as well as the data science methodology. It aims to provide an informal bridge between clinicians, charities, and data owners (like CRIS, UKDP, and Biobank) and data science researchers to stimulate and align cutting edge research in this area.
Events
Meetings
We organise monthly meetings (including half-an-hour long invited talks) at the Turing. Meetings are organised and moderated by Jenny Chim, Yue Wu, and Emilio Ferrucci. Please join our mailing list for more updated information.
As a part of AI UK Fringe, we jointly organised a hybrid event with the NLP interest group on AI for Mental Health Monitoring on 28th March 2024.
See here for our previous talks.
Upcoming Events
Meetings
| Date | Time | Presenter | Title |
|---|---|---|---|
| 2024.07.18 | 15:00 | Introduction | |
| 15:05 | Vasudha Varadarajan (Stony Brook University) |
ALBA: Adaptive Language-based Assessments for Mental Health
Language-based assessments are promising for capturing diverse mental health diagnoses but need many words per person for accuracy. This talk introduces Adaptive Language-Based Assessment (ALBA), which adapts future prompts based on previous responses. ALBA iteratively selects the next best question to refine the estimate of an individual's psychological traits using limited responses. ALBA paves the way for conversational diagnostic agents, enabling dynamic scoring and personalized interactions. This approach improves diagnostic accuracy, reduces time for patients and clinicians, and enhances personalization in assessments. |
|
| 15:45 | Dr. Guy Laban (University of Cambridge) |
Social Robots as Communication Partners to Support Emotional Health and Well-Being
As society increasingly integrates artificial intelligence (AI) technologies designed for social interaction, understanding the communication dynamics between humans and social robots becomes essential. In this talk, I will present my research that explores the intersection of AI and human interpersonal communication. My studies focus on the dynamics of human-robot interaction, particularly how robots can foster meaningful social interactions that encourage users to express their emotions and feelings. In my research, I study how these interactions evolve over time, their potential for supporting emotional well-being, and their application in various settings such as caregiving and counselling. Through a series of experiments, my research uncovers the nuances of dialogue, self-disclosure, and emotion regulation in the context of social relationships with robots. The findings illuminate the varying degrees of emotional engagement exhibited towards robots, including how individuals adapt to and become comfortable with them over time, share their emotions, and experience positive effects in supporting their well-being. |
|
| 16:20 | After talks discussion |