If you are an MSc, BSc, Ph.D., or postdoctoral student who would like to collaborate with our lab on your research project or conduct an internship with us, you are on the right page! Depending on the depth and duration of your project, the project focus will be adjusted. When you see a thesis project you want to pursue with us, please complete the Your Turn section at the bottom of the page.

Improve behavior, health, and life quality for everyone, one project at a time!

What you Get

A ticket to a journey of high-quality research and development, with a successful bachelor’s, master’s, PhD, or post-doctoral research/internship in computer science or a related field on the way. Collaboration between Geneva (Switzerland), Copenhagen (Denmark), and Stanford (USA) teams, as well as collaboration with industry partners and international organizations, as well as other stakeholders in the well-being, health, and quality of life domain, are implied. An international visit abroad – to spend some time with the project collaborators is always an option. The potential projects are as follows.

1. Say versus do – longitudinally (in)validating validated self-reported life quality measures 

For many behaviors (e.g., physical activity, sleep, nutrition) and personal states (e.g., conditions such as depression and anxiety, level of social support), over time, researchers have calibrated and validated diverse questionnaires “in the office”. However, few studies have tested the validity of such questionnaires when correlated with data collected from daily life “in the wild”.

Scope: Research, design, development, deployment, analysis, and discussion of a comparative study between the outcomes obtained through the administration of a validated scale and those obtained through the collection of analogous wearable data.

Skills: Programming skills, knowledge of statistics, exposure to participatory design, and an inclination towards applying these in the health sciences.

Team: The coordinator is Katarzyna Wac, leveraging the collaboration with validated scale experts at the University of Copenhagen. Teams of students are welcome.

2. mQoL Living Lab: Empowering big data for QoL improvement

Our living lab aims at leveraging smartphones and wearables to collect data from daily life, in time and context, over long periods of time. Such data does not only refer to the “usual” data an activity tracker may collect from the participant: the number of steps (physical activity), hours slept (sleep), or heart rate (health state). Aspects of daily life can also be assessed with validated questionnaires (e.g., stress and anxiety) and serious games (e.g., attention levels and reaction time).

Scope: Development, deployment, and discussion of deep device instrumentation features for our Flutter (iOS and Android) mobile platform. This mQoL lab app is already under development and is based on our Android mobile platform.

Skills: Very strong programming skills, particularly in Flutter, and interest in exploring Flutter frameworks used in mobile health contexts.

Team: The coordinator is Katarzyna Wac, leveraging the collaboration within the Quality of Life technologies lab, particularly Igor Matias (University of Geneva). Teams of students are welcome.

3. Peer-ceived stress in situ

Are you stressed? Besides being a relevant question to ask nowadays, this is a recent study in our lab. The study explores the relationships between the state-of-the-art stress assessment by using validated scale-based questionnaires that are self-administered by the participant and the stress assessment by using exploratory questionnaires that are administered to the participant’s peers (friends, family, co-workers) in situ.

Scope: Design and development of a mobile platform for peer stress assessment on the iOS platform, consisting of two applications: one for the individual and one for the peers.

Skills: Good programming skills, particularly in the Apple iOS universe, and an interest in exploring iOS frameworks used in mobile health contexts, such as HealthKit and ResearchKit.

Team: The coordinator for this thesis is Katarzyna Wac. Currently, the study is being replicated at Stanford (USA). Teams of students are welcome.

4. Migraine assessment and predictions in situ

Migraine is a debilitating disease, and migraine headaches decrease the quality of life of individuals suffering from it, as well as those around them. Is there an influence of behaviors on the migraine headache attack? Can we predict the next attack, given enough data about the past behaviors of the individual? Can we model and predict the behaviors, well-being, and quality of life of migraine sufferers longitudinally? We identify a set of new research questions in our lab, which we hope to answer in collaboration with MigraineBuddy team – developing and continuously improving their award-winning app-based migraine headache diary and tracking platform. The app helps users record and identify triggers of migraines, symptoms, medication, migraine frequency and duration, pain intensity and location, and other lifestyle factors to help users improve their migraine condition.

Scope: The first stage implies an analysis of already collected datasets. The second stage implies an analysis of data for selected cohorts of individuals – being already MigraineBuddy users in Denmark/Switzerland/USA.

Skills: Good statistical background and programming skills for large datasets analysis (Python, R, Matlab).

Team: The coordinator for this thesis is Katarzyna Wac, leveraging the collaboration within the MigraineBuddy Development team (Singapore and France). Teams of students are welcome.

5. Behaviours, health, well-being, quality of life – What really matters for the general public and why? And what matters to you?

How does an average individual perceive their own behaviors, health, well-being, and quality of life? What matters to him or her? What do they define as ‘good’ behaviors and ‘bad’ behaviors, and why? Do they use technologies like wearables and apps for the self-management of health? Given an increased human lifespan, along with an increased burden of chronic illness, we ask these questions to ourselves and populations at large. We identify a set of new research questions in our lab, which we hope to answer in collaboration with scientists from Stanford Prevention Center (USA), specifically focusing on data collection via WELLforLife platform. 

Scope: QoL-lab-specific expansion of the existing self-report-only based WELLforLife platform, especially incorporating the wearables and smartphone mhealth apps-enabled data collection for individuals. The first stage implies an analysis of already collected datasets. The second stage implies an analysis of datasets collected from selected cohorts of individuals in Denmark/Switzerland/the USA.

Skills: Good statistical background and programming skills for large datasets analysis.

Team: The coordinator for this thesis is Katarzyna Wac, leveraging the collaboration within the Stanford Prevention Center (USA). Teams of students are welcome.

6. Behaviours, health, well-being, quality of life – Who are the ‘changemakers’? Are you one of them?

What social structures in which we live and operate daily guard or enable our momentary ‘good’ behaviors and ‘bad’ behaviors? Who are the changemakers enabling better individual behaviors and hence a better world? Who do the individuals listen to when not in touch with the healthcare system because they are not really sick? Given the burden of chronic illness, aging, and sustainability, the world now requires everyone to be a changemaker. Along with that statement, we identify a set of new research questions in our lab, which we hope to answer with collaborators and from Ashoka and LinkedIN Elevate teams (both in the USA). The larger context of this project relates to the IEEE Standardization activity on Social Impact Measurement (SIM), to which QoL lab has contributed since August 2019.

Scope: QoL-lab-specific expansion of the existing Ashoka/LinkedIN approach for human networks analysis and “changemaker score” metrics, especially incorporating the QoL-lab-specific mobile app (Android/iOS) for self-assessment of behaviors and social context. The first stage implies an analysis of already collected datasets by LinkedIN/Ashoka. The second stage implies an analysis of datasets collected from selected cohorts of individuals in Denmark/Switzerland/the USA.

Skills: Good statistical background and programming skills for large datasets analysis (Python, R, Matlab).

Team: The coordinator for this thesis is Katarzyna Wac, leveraging the collaboration within the Ashoka and LinkedIN Elevate teams (USA). Teams of students are welcome.

7. Measuring Social Impact, but How?

From the Organization for Economic Cooperation and Development (OECD) report on Social Impact Investment January 2019 “Social impact investment is the provision of finance to organizations addressing social needs with the explicit expectation of a measurable social, as well as financial, return. Social impact investment seeks to leverage innovation and apply measurement rigor to achieve social outcomes.” The challenge is that the ‘measurable social return’ is hardly measurable, as the reliable and reproducible set of impact measures, formulae, logic models, and processes for assessing and calculating social impact hardly exist today. For example, there are 150 social impact platforms uncovered by the Bertelsmann Foundation 2018 report, each having a different measurement framework. Then there are a set of other metrics proposed by the Open SDG Data Hub aiming to facilitate reaching the UN Sustainable Development Goals (SDGs) by 2030. Our lab has a high ambition to achieve a substantial social impact in the future, and we are interested in contributing to existing research and development in the domain of social impact measurement. Along with that statement, we identify a set of new research questions in our lab, which we hope to answer with collaborators and from Ashoka (USA). The larger context of this project relates to the IEEE Standardization activity on Social Impact Measurement (SIM), to which QoL lab has contributed since August 2019.

Scope: A research on the existing set of impact measures, formulae, logic models, and processes for assessing and calculating social impact, starting from the Bertelsmann Foundation 2018 report and the Open SDG Data Hub and continuing with the analysis of other datasets documenting past and existing projects worldwide. The datasets are provided by our collaborating teams. 

Skills: Good qualitative research skills especially applied for large datasets coding/analysis.

Team: The coordinator for this thesis is Katarzyna Wac, leveraging the collaboration within the Ashoka and IEEE Standardization activity on Social Impact Measurement (SIM) (USA). Teams of students are welcome.

8. Chronic disease longitudinal risk assessment

The top killers worldwide are chronic diseases, such as cardiovascular disease, lung disease, and diabetes. Existing risk assessment models can calculate the risk of such diseases, yet some of the risk factors (age, gender, smoking status, presence of diabetes, body mass index, blood pressure, glucose, and cholesterol) are hard to obtain.

Scope: Design, development, and deployment of a mobile platform that enables the data collection for these risk factors in a large population (n > 10.000), or analysis of the existing datasets we already have collected for tens of participants (age, gender, smoking status, presence of diabetes, body-mass index, glucose, additionally to sleep, physical activity, heart rate).

Skills: Strong programming skills, knowledge of statistics (specifically for the second choice within the thesis scope), exposure to mobile platform development (preferably iOS), and an inclination towards applying these in the health sciences.

Team: The coordinator is Katarzyna Wac, leveraging the collaboration with the “L’unité d’éducation thérapeutique du patient” at the Geneva University Hospitals (HUG). Teams of students are welcome.

9. If you continue like this… scenarios for a chronic disease

More than 40% of the risk of chronic diseases is due to unhealthy behaviors, such as physical inactivity, bad nutrition, poor sleep, or smoking status. However, there is no precise cause-effect formula that translates all these behavioral “markers” to the risk factors used in the risk assessment models from the literature.

Scope: Research, development, and deployment of an interactive scenario generator based on the latest results in chronic disease risk assessment, longitudinal behavioral and health data from a large sample of the Danish population, and behavioral and health data from a participant.

Skills: For this thesis, it is important that the candidate has strong programming skills, knowledge of descriptive and inferential statistics, exposure to data visualization, and an inclination towards applying these in the health sciences.

Team: The coordinator is Katarzyna Wac, leveraging the collaboration with the “L’unité d’éducation thérapeutique du patient” at the Geneva University Hospitals (HUG). Teams of students are welcome.

10. Quality of Life Chatbot UX/UI design

Our lab is implementing a chatbot to make participation in scientific studies fun! The chatbot is in the minimum viable product stage: it can sign up people for studies, follow up with research questions, and connect with the participants’ wearable for health data sharing, all using the Facebook Messenger platform. It contains a few explorations: Explore Your Physical Activity, Explore Your Sleep, Explore Your Stress, and Explore Your Quality of Life.

Scope: participatory design sessions of the chatbot with users (researchers and participants) and concrete user interface design; exposure to user data-driven (analytics) research; psychological aspects of chatbot engagement and human study participation.

Skills: excellent design skills, particularly in user experience (UX) and user interface (UI) design, and an interest in taking a research-driven approach to co-designing / participatory-designing (PD) a chatbot.

Team: The coordinator is Katarzyna Wac. Priority will be given to design students. Teams of students are welcome.

11. Improving Quality of Life in Geneva

Our lab is collaborating with Maison Quartier Plainpalais to understand the needs, wishes, and visions of the Plainpalais area – a very dense and diverse area in the heart of Geneva. We collaborate with the city and canton on the assessment and improvement of the quality of life of its residents. 

Scope: participatory design sessions with Plainpalais residents and policymakers, enabling to derive their needs and solutions for the quality of life assessment and improvement.

Skills: excellent co-design skills and an interest in taking a research-driven approach to co-designing / participatory-designing (PD) of real-world solutions. French language.

Team: The coordinator is Katarzyna Wac. Teams of students are welcome.

Your Turn

Please answer all questions below. Use as much or as little detail as you find appropriate. The answers should be returned via email to Prof. Katarzyna Wac. We reserve the right to be unimpressed if you cannot follow these simple instructions. We also encourage projects in teams, so if you have a friend or two who are interested, you can write a thesis together and join forces to improve health for everyone!

* Questions:
Q1: What is your study line (if this question applies to you)? What is the scope of the project you are looking for: PhD, MSc, BSc, internship, or other?
If applicable: Do you have financial support for the project, or do you look for a paid position?
If applicable: What is the deadline you need to apply to get financial support for the project?
Q2: What is the timeline for the project itself (START, STOP)?
Q3: List your programming experience (e.g., standard machine learning libraries (e.g., sk-learn, pandas, PyTorch, and TensorFlow/Keras) and/or data visualization software (e.g., Plotly, Seaborn, Matplotlib))
Q4: List your math courses & skills
Q5: List other skills that you consider relevant
Q6: What is the best class you have taken at CUI/DIKU/Your University* and why?
Q7: What is the worst class you have taken at CUI/DIKU/Your University* and why?
Q8: What project from the above list interests you the most and why?
Q9: What grade do you aim to receive for your project and why? (if the project is graded)
Q10: Please attach your up-to-date CV (and publication list, GitHub link, and other resources that apply to you).

*depending on where you are based: UNIGE/CUI, UCPH/DIKU, or other universities.

Email: katarzyna.wac@unige.ch

p.s. Above instructions are totally inspired by Prof. S. Lehman, DTU

The Ongoing and Past Theses