What specifically are you researching at the new faculty in Kulmbach?

We combine computer-based and natural science approaches to investigate how humans and machines can learn and control goal-directed complex behaviour. The Digital Health research group in Kulmbach is an important pillar of a cross-border laboratory at Imperial College London and the University of Bayreuth. Our topics of interest are AI for Healthcare, i.e. learning decision systems in hospitals, telemedicine, AI-supported health interventions at home and in care, etc. Then Human Augmentation with a focus on the restoration of mobility and motor skills of the hand or arm after illness, accident, or ageing through robotic systems, the support of cognitive skills in the home and on the move (cognitive prosthetics), as well as through robotic-digital support of patients at home and in care facilities. In addition, Human-AI Interaction with core objectives in the area of Explainable AI and Trusted AI, which are essential if artificial intelligence is to become a valuable individual "agent" in medicine and in society that supports and is trusted by people. And finally, there are the foundations of AI: prioritising Deep Reinforcement Learning, embedded AI, Causal Inference in Machine Learning, and the knowledge integration and context integration of biomedical and non-biomedical data.

What do you see as the potential benefits of this research?

Artificial intelligence and specifically machine learning represent the most profound change in how humanity is generating innovation since the invention of fire and the wheel. For the first time, solutions and innovations are not being built by hand by engineers and inventors, but are being learned directly by machines using data. This approach holds the greatest potential for society as a whole in the field of health and medicine, as increasing digitalisation makes huge amounts of data available worldwide that can be used to help people specifically in the prevention, detection, treatment, and rehabilitation of diseases and age-related problems.

Are there any exciting projects coming up in Kulmbach?

The Kulmbach Living Lab. It is a research project that is unique in the EU in which engineers, computer scientists, behavioural and natural scientists dedicated to analysing human behaviour and developing new technologies for a healthy long and independent life will observe the behaviour of people. Using ideas from our existing Living Lab in London, we’re taking them to the next level in Upper Franconia. For example, motion sensors in a specially equipped flat will record how often a person goes to the fridge during the day, what they then eat, and whether they take health aspects into account. We will announce details of this later.

Personal Details

Aldo Faisal im Büro Kulmbach

After taking his A-levels and studying computer science in Germany, Faisal went to Cambridge University as a scholarship holder of the German National Academic Foundation to study biology, where he later earned his PhD in Computational Neuroscience and became a Fellow of the University in the Faculty of Engineering. In 2009, he moved to Imperial College London to set up his own lab, following appointments as Associate and later Full Professor. Faisal was Director of the Behaviour Analytics Lab at the Data Science Institute in London and founding Director of the UKRI Centre for Doctoral Training in Artificial Intelligence for Healthcare. He continues to conduct research in London. He also directs collaborations in the field of AI with TU Munich and BW. He has held his professorship in Kulmbach since January 2022.

Background: AI (Artificial Intelligenc) & Health

AI for Healthcare: learning decision systems in hospitals, telemedicine, AI-assisted home and care health interventions, etc.; Human Augmentation with a focus on the restoration of mobility and motor skills of the hand or arm after illness, accident or ageing through robotic systems, the support of cognitive skills in the home and on the move (cognitive prosthetics), as well as through robotic-digital support of patients at home and in care facilities; Human-AI Interaction with core objectives in the area of Explainable AI and Trusted AI that are essential if AI is to act in medicine and in society as a valuable individual "agent" that supports people and who are to trust AI; Foundations of Artificial Intelligence: prioritising Deep Reinforcement Learning, embedded AI, Causal Inference in Machine Learning and knowledge integration and context integration of biomedical and non-biomedical data.

Prof. Dr. Aldo FaisalProfessorship of Digital Health with a focus on Data Science

Faculty of Life Sciences: Food, Nutrition and Health
University of Bayreuth - Campus in Kulmbach
Phone: +49 (0) 9221 / 4071162
E-mail: aldo.faisal@uni-bayreuth.de

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