Interdisciplinary Research Projects

Interdisciplinary Research Projects

This searchable database contains details of pump-primed cross-discipline research projects taking place at the University of Aberdeen.

One of the main strands of our Aberdeen 2040 plan is to address urgent and wide-ranging challenges in the interdisciplinary areas of Energy Transition, Social Inclusion and Cultural Diversity, Environment and Biodiversity, Data and Artificial Intelligence, and Health, Nutrition and Wellbeing.

The wide range of projects on display here is a demonstration of some of the early-stage research being funded in these critical areas as well as the University's commitment to addressing the UN's 17 Sustainable Development Goals, a "blueprint to achieve a better and more sustainable future for all."

Projects undertaken in 2021 were funded by the University of Aberdeen's Scottish Funding Council allocation.

Page 1 of 3Results 1 to 10 of 22

Human robot interaction network

Robotics and AI are at the forefront of the current fourth industrial revolution. The acquisition and deployment of Pepper, a humanoid robot designed for human robot interaction, will allow academics across the University to collaborate in this area of growing research importance.

An interdisciplinary approach to generate a paradigm shift in characterising biodiversity

Biodiversity plays an integral role in ecosystem function, health and service, but this is threatened by the unprecedented loss of species. To combat the global biodiversity crisis, we need to better understand diversity at all levels of organisation.

Citizen science for biodiversity conservation in agricultural-conservation transition zones

Citizen science has grown rapidly in popularity in recent years due to its potential to educate and engage the public while providing a means to address a host of scientific questions. Here, we aim to elucidate biodiversity patterns and associated human-wildlife conflicts in agricultural conservation transition zones.

Mathematical model of hospital patient flow

One of the biggest challenges that hospital management teams face is the uncertainty of when patients will be admitted to and discharged from hospital. Now, a groundbreaking mathematical model will help predict the length of a patient’s stay in order to help optimise patient flow.

How to involve the public and patients in data-intensive research?

Patient and public involvement (PPI) in studies can improve their relevance and impact. Our aim is to identify the best ways to involve PPI in data-intense health research.

A pilot study to estimate glacier surface velocities for ice avalanche events

Glacier ice avalanches present a series of hazards to those living in the vicinity of high mountains. By constantly monitoring data we should be able to estimate surface velocity changes and predict potentially catastrophic events before they happen.

Visual processing in humans and machines

Neuroscientists have argued that machine vision techniques have significant similarities to the human visual system, which has immense implications for technological advancements and our understanding of the human brain. But is this actually the case? By building simple artificial neural networks we aim to find out.

Autonomous robotic sampling of bio-aerosols for real-time DNA sequencing using MinION sequencer

Bioaerosols are tiny airborne particles originating from plants or animals, and human exposure to them comes with potentially serious health risks. We propose using a portable sequencer to determine their source and composition in order to control and regulate potentially dangerous emissions.

Individual facial biological age estimate for healthy ageing

Is it possible to track an individual’s biological age through changes in their facial features? We are developing an individual facial biological age estimate framework to try and find out.

Assessing the impact of 3D terrain data resolution on thermomechanical modelling of ice avalanches

In February 2021, an ice-rock avalanche-triggered flash flood in India killed over 200 people and destroyed two hydroelectric plants. We studied the impact of terrain data quality on the thermomechanical modelling of avalanches and discovered the reason for the event’s magnitude, with implications for future data use.
Interdisciplinary Challenges

Clear Filters