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Staff Profile

Professor Lucy Asher

Professor of Behaviour Informatics

  • Telephone: +44 191 208 4638
  • Personal Website: asherbehaviourlab.com
  • Address: School of Natural and Environmental Sciences
    Room 608
    Agriculture Building
    Kings Gate
    Newcastle University
    Newcastle
    NE1 7RU
Background

My research concerns using patterns in behaviour to earlier detect good and poor welfare states or events. 

In the modern world computing technology is used for surveillance of human behaviour. By looking at the patterns of peoples' movements from CCTV footage, computing systems can detect those about to commit antisocial behaviour, violent acts or contemplating suicide. The main advantage of such techniques is that they can predict such unpleasant events before they happen. This means some of these events can be prevented.

I apply the study of patterns of behaviour to animals. I use statistical and computing techniques, but am very much grounded in ethology. Prediction of positive or negative welfare states and events using computing technology is likely to become increasingly important as the hundreds of billions of animals in human care increases further still. It is important that this area is led by an understanding of animal behaviour and welfare rather than the availability of technology. Yet computing and statistical techniques also have much to offer the study of behaviour. Patterns in behaviour can be used to automatically create ethograms, based on behaviour shown by animal and precise measurements of movement. Extremely subtle changes in behaviour can be detected which would not be apparent to the human observer. Behaviour over long time scales can be studied and normality or abnormality defined for each individual. These are the types of challenges which have interested me throughout my career.

I trained in Zoology and Psychology at Bristol and completed an MSc in Animal Behaviour at Edinburgh, before commencing a PhD on starling welfare with Professor Melissa Bateson. Through my PhD on starlings, I studied sequences in behaviour using a Markov chain approach. A post-doctoral position at the Royal Veterinary College followed, where I used novel methods to quantify patterns of group behaviour in hens. For the five years which followed I was based at the School of Veterinary Medicine and Science at the University of Nottingham, first as a Lecturer and then Assistant Professor. During my time at Nottingham I used statistical approaches to measure  'The Epidemiology of guide dog behaviour' in a large scale 5 year research project. I also worked on a range of other projects relevant to animal welfare in a variety of species; from poultry to elephants. 

In 2015 I moved to Newcastle University to take up a position as Senior Newcastle University Research Fellow and in 2019 took a Senior Lectureship. I was promoted to Professor in 2021. I continue to work on patterns in behaviour, primarily focusing on domestic poultry and dogs. A list of current projects can be found on my Research page.

Research

I have two main streams of research at Newcastle University, as well as involvement in a number of other projects looking at patterns of animal behaviour.

DogBox- we are developing high-tech ways of recording and measuring dog behaviour and welfare. We use inertial sensors and video footage to record dog behaviour and movement and use statistical and computational methods to determine which movements and which behaviour is associated with good and poor welfare states. We are interested in how behaviour changes over time and how predictable or random behaviour becomes under stress.


ChickenWatch- we research automated measurements of chicken health and welfare using vision-based techniques and acoustic monitoring. Using the patterns of movement a chicken makes over time, the thermal readings of an individual or flock, or the calls an individual or flock make, we can tell a lot about how a chicken's welfare. 

Teaching

I contribute to the MRes courses in the Faculty of Medical Sciences and supervise postgraduate students.

Publications