Prospective Students

This page contains information for students who are interested in having me supervise their thesis.

General

I encourage you to focus on a research question: What is it that you want to find out? From this question flows everything else – methods, literature review, experiment hypotheses, app designs. It’s normal for a research question to be quite vague in the beginning, and to be refined later on.

I encourage you to make your thesis your own as much as possible. The project proposals I set are departure points – I expect you to do your own research and shape your own research question.

I expect you to be able to use Google Scholar (at the very least) to search for relevant literature on your topic.

If I have more than two or three Masters or Undergraduate students from the same programme at the same time, most of your supervision will be in group meetings (in person or online). 1:1 supervision will be mainly online, but I will try to meet with you 1:1 in person once every four teaching weeks.

I travel a lot. That is both good (lots of interesting potential for collaborations) and bad (I won’t be able to see the students whom I supervise in person every one or two weeks). Therefore, I work a lot online. I have my own Slack team to which I invite all my students, with channels for undergrads, masters, and PhD students. If you ask me a question on Slack, I usually respond quite quickly. Email can get lost in a morass of other emails, and I tend to have Skype open only when I’m expecting to receive or make a call.

Perhaps most importantly – doing a thesis is hard work. It will push you to your limits. If you have any worries, if you find yourself staring at a blank screen, getting depressed or anxious, if you don’t know how to cope, if you’re lost, talk to me. You are not weak. This happens to loads of people. There is plenty of help, and there are no prizes for suffering.

Undergraduate

(UG4 Informatics / UG4 Cognitive Science / Masters in Informatics)

I am happy to supervise projects that focus on user evaluations, experiments with users, and human-computer interaction. We will look at ways of reconciling your project work with your course work, because often, the thesis suffers under a barrage of course deadlines, even though it is worth far more in the grand scheme of things.

Typically, I expect my students to take the Human Computer Interaction course or to have some background in Cognitive Science and psychology.

I can take on a maximum of 7 undergraduate / MInf students at a time.

MSc Students

(Design Informatics / Artificial Intelligence / Cognitive Science / Global eHealth / Human Cognitive Neuropsychology / Cognition, Science, and Society / Speech and Language Processing)

I supervise projects that involve laboratory experiments, systematic reviews of the literature, user evaluations, and apps that are co-designed and evaluated with users. I have expertise in eHealth and general wellbeing, and to some extent in social media, mental health, accessibility, and general human-computer interaction. If you want to code, I expect you to have coded at least one larger project yourself, and I may ask you to show it to me.

Informatics students can choose from a range of topics I’ve proposed on the main project proposal site. If you are a student on another MSc programme, contact me (maria dot wolters at ed ac uk) with your idea.

I’ve taken on MSc students from a wide range of programmes and all three Colleges of the University.

My capacity limit is 10 MSc students at a time across all Colleges and programmes I work with.

PhD Students

I supervise PhD projects that are closely linked to my own research, in particular around mental health and wellbeing, and making life better for people who live with chronic health issues.

PhDs are a rite of initiation into the process of doing original research. As your supervisor, I will do my best to help you figure out who you are as a researcher, produce work you can be proud of, stay (more or less) sane throughout the process, and have fun exploring uncharted territory. We will also look at life after your PhD, making sure that you emerge with transferable skills that will help you wherever you decide to go next.

For a PhD, a good fit between supervisor and student is far more important than for a Masters project, so here’s some more information about how I supervise. If I’m your principal supervisor, expect to get this approach pretty much unfiltered; if I’m your co-supervisor, I will work closely with the principal supervisor.

  • I want you to question everything. I’m not interested in projects that just apply the latest Machine Learning technique to a convenient data set (or apply Machine Learning to a problem without knowing where the data will come from). I want you to think about where the inputs come from, what the outputs actually mean, what the limits of the data are.
  • You will need to acquire new skills and go into new literatures. I will support you as much as I can – with courses to audit, readings, or quick tutorials.
  • I expect you to get to know the literatures in your field very well. We may even start out with a comprehensive narrative or systematic literature review as your first larger piece of work.
  • I will encourage you to think for yourself. When you ask me a question, I will often turn it back over to you to see what your own thinking on the issue is.
  • I will challenge you to defend your approach and conclusions. I am also easily persuaded that you’re right, if you make a good case.
  • If you use quantitative methods to work on a topic, I expect you to be able to (or at least learn how to) program in R and at least one scripting language of your choice. I prefer Python, but that’s because it’s what I use for coding. I know that R is a pain in the neck to learn, but this is a School of Informatics.
  • Everybody has their own slant on research, their own preferences, which won’t completely match with mine. Some degree of mismatch is healthy, stimulating, and productive; if the mismatch is too great, though, I am happy to help you find an alternative supervisor.