CSIUS Researcher: Dr Marcus Winter
Why did you become a researcher?
It’s the most interesting calling I can think of. Exploring, experimenting, learning, sharing, and getting paid to do it – count me in! I had a professional career before starting at University, which involved both technical development and human-computer interaction research. Transferring that to an academic context was only a small step. I’m still building technical prototypes and research how people interact with them. But instead of then polishing and proofing applications for production, I now focus on evaluating them, and conceptualising and disseminating findings.
Describe a typical day at work
Luckily, there is no typical day at work. However, there are days which are more similar than others. For example, there are teaching days, where I give lectures and tutorials, supervise research students, prepare teaching materials, mark assignments, etc. And then there are research days, where I meet with people, develop prototypes, plan and carry out user studies, or write up findings for publication. You probably can guess which days I prefer.
Who has influenced you most in your research career so far and how?
I’m more influenced by ideas than by people. Early on in my research career, someone pointed out to me that even if a project fails to achieve its objectives, it can still be successful in research terms, as looking at the reasons behind the failure can provide insights into the problem at hand. While this seems obvious now, it was an eye-opener for my former self coming from commercial development, where failure is not an option. Another idea that stuck with me, is that sometimes, zooming in on the tiniest details is key to getting the bigger picture. I still remember a conference presentation where a prominent human-computer interaction researcher talked us through a super slow-motion video, dissecting in minute detail an interaction sequence. Brilliant and extremely interesting! There are many other ideas that have influencing me as a researcher – too many to discuss here.
What is the greatest challenge you have ever undertaken?
Starting from scratch. I have done that several times. Emigrating from Germany to Italy in the mid 80s (only to go bust after a year) and to the UK in the mid 90s. Building careers first as a software developer, then an entrepreneur, now an academic researcher. Starting from zero with little or no support is challenging but also very exciting.
What is your greatest achievement?
Bringing up a wonderful daughter, while working fulltime and doing a part-time PhD.
If you could invite three people to dinner (past or present), who would they be?
Sally Sedgwick – a hugely impressive contemporary philosopher I could listen to all day.
Leonardo da Vinci – what ideas would he come up with looking at today’s technologies?
David Attenborough – I’d beg him to take me on one of his journeys into the wild.
What is the best bit of advice you’ve ever received (work or personal)?
Be kind to people, everybody has their problems we don’t know about
What would be the research project you’d most like to work on?
Pretty much what I’m doing now: exploring how emerging technologies can be used to engage and empower people. Ideally I would do this with a larger budget though – supporting lab space, a small team of researchers, developers and designers, and me to work on it fulltime!
My current research:
I’m currently working on a collaborative project with The Regency Town House, exploring how interactive applications of machine learning can support visitor engagement in museums.
Machine learning has made enormous progress over the past decade or so, giving computers all sorts of new capabilities they didn’t have before. But what can we do with these capabilities? What new kinds of interactions do they afford? How to deal with problems inherent in machine learning, such as bias and uncertainty? Our project explores these questions in a heritage context.
This work is important as it fills a gap in current understanding, and provides museums with new tools and engagement models to support their ongoing evolution from organisations preserving the past to places for informal learning. Technology can play an important role here, drawing in new audiences and enabling people to learn through active exploration and participation.
We have so far evaluated two prototypes in empirical studies, where machine learning models for human pose estimation and gesture recognition were used to enable visitors’ engagement with interior designs and wall decorations. Our preliminary findings are very encouraging and confirm the great potential of these technologies for visitor engagement.
