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Department of Informatics People and Computing Lab

Digital Health and Personalization


Understanding the lived experience of individuals with chronic conditions has been of much interest in the Human-Computer Interaction (HCI) community. Living with a chronic condition, like type 1 diabetes (T1D), comes with many challenges and effective self-management is crucial to avoid serious health complications, such as diabetic retinopathy and lower-extremity amputations. Self-management of chronic conditions is mostly done by the patients themselves and is highly individual. Idiosyncratic reactions to activity, medication, food intake and others make self-management challenging, personal and experience based. Thus technologies designed for individuals living with a chronic conditions need to account for this personal differences and empower patients in sharing their experiential knowledge.

Our Research

Our research revolves around the design and development of digital health technologies tailored to the individual needs of people living with chronic conditions, with a particular focus on T1D. Drawing upon approaches from Human-Computer Interaction and Visual Analytics, we aim to understand:

  1. Where is the need for personalization in T1D self-management and how could technology support that?
  2. What kind of personalization is desired and how could personalized technology improve the lives of people living with chronic conditions.
  3. How can we design and develop personalized solutions that meet the individual needs of people living with chronic conditions?
  4. How can we leverage the experiential knowledge of T1D self-management in AI powered solutions? What kind of balance should be achieved between human and machine control?
  5. What is the efficacy of personalized disease management technology, and how does it affect the lives of people with chronic conditions?


If you are interested in doing a master thesis, master project, bachelor thesis or independent study related to one of my topics or the personalization of digital health technologies in general, please contact me here after reviewing the application process and requirements here.

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Using the Past to Inform the Future

More about Using the Past to Inform the Future

In this ongoing project, we explore the benefit of seeing analogous past situations for informed chronic disease management decision-making.

Blood Glucose Prediction

More about Blood Glucose Prediction

In this project, we focused on understanding the lived experience of individuals with type 1 diabetes (T1D) using personalized blood glucose predictions in their everyday lives.

Differences as Personalization Opportunities

More about Differences as Personalization Opportunities

In this ongoing project, we explore the differences in T1D self-management to understand the opportunities for personalization in T1D self-management.

Personalizing One Aspect

More about Personalizing One Aspect

In this ongoing projects, we explore how one aspect of a chronic disease management application can be personalized. This could be related to nutrition tracking, medication-tracking, notifications, physical activity, adherence motivation etc.