Uncategorised / Friday, 14 July, 2017

Kelvin Tsoi – LIDA Visit


I’m Kelvin Tsoi, a digital epidemiologist from the Stanley Ho Big Data Decision Analytics Research Centre, the Chinese University of Hong Kong. I am leading an interdisciplinary research team to apply Big Data techniques for healthcare research. I visited Leeds Institute for Data Analytics (LIDA) and shared my recent research work on Artificial Intelligent Application for Dementia Screening.

This was a wonderful experience to visit LIDA, as I saw a very strong interdisciplinary research institute with professionals from different academic backgrounds, including medicine, engineering, geography, and also business. I spent much of my time to visit different research groups to explore the collaboration. I had a chance to walk around the LIDA and also the campus. The University of Leeds is a beautiful and traditional place to study. I also had a chance to visit the city and jog in the morning to breathe the fresh air in Leeds.

The presentation in the LIDA seminar was also an important chance to deliver our updated research in front of a group of academic experts and professors. All comments and discussions were valuable to improve our research ideas and future directions. It was also a golden chance to explore the collaboration in Asia.

In my visit, we had discussed some preliminary collaboration plans. i.e. Dr. Michelle Morris and I will work together for a collaborative proposal on digital health for non-communicable diseases. We will also try to identify external funding to support our initial research collaboration. Besides, I also met Dr. Owen Johnson, and followed-up a previous project under the Worldwide Universities Network. We came out a clear picture on the communicate gaps across professionals from different academic backgrounds when we worked as an interdisciplinary research team. The discussion was fantastic to summarize the experience that we learnt, so we planned to write up some viewpoints and hope it will be a useful reference to those who are engaging in the novel field of interdisciplinary work.

In short, the experience of my visit was fruitful and constructive to my career. I would recommend this type of engagement activity to other scholars if they want to learn more updates on data sciences from the angles of interdisciplinary research.