Dr Inna Skarga-Bandurova
Prof., Doctor of Science
Dr Inna Skarga-Bandurova is a Senior Lecturer in Artificial Intelligence at Oxford Brookes University. She is also a visiting Professor at the Pukhov Institute for Modelling in Energy Engineering (PIMEE), National Academy of Science of Ukraine.
Inna received MEng in electronic engineering from East Ukrainian National University (EUNU) and a PhD in computer science from Donetsk National University, Ukraine. In 2015, she completed her D.Sc. habilitation and was nominated to the professorship of Computer Science and Engineering (CSE). Dr Skarga-Bandurova directed EUNU's Health Informatics Research Group and Artificial Intelligence Research Group for a decade and served as the Head of the CSE Department at EUNU.
In 2019, she joined the Visual Artificial intelligence Research Lab at Oxford Brookes University and conducted research in automated reasoning and decision-making for the smart autonomous robotic assistant surgeon.
Areas of expertise
- Modelling decisions for Artificial Intelligence (AI)
- Automating AI for decision-making
- Automated reasoning
- Formal methods for data analysis in different areas of application (critical infrastructure, healthcare, smart environments, environmental studies, complex human-machine systems, etc.)
Teaching and supervision
- Artificial Intelligence (BSc (Hons), MSci)
- Artificial Intelligence (MSc, PGDip, PGCert)
- Computer Science (BSc (Hons))
- Innovative Product Development (Module leader)
- Advanced Artificial Intelligence
- Introduction to Machine Learning (Module leader)
- Advanced Machine Learning (Module leader)
- Data Analytics and Machine Learning (Module leader)
Dr Skarga-Bandurova's current research focuses on the fusion of AI components as speech, vision, perception, and the use of machine learning, reasoning and autonomous decision-making for simulation of human intelligence by computer systems.
Inna Skarga-Bandurova has consulted for companies on strategic use of information technology in areas including data mining, clinical decision process automation, information security analysis, group decision making and prediction.
Her research group develops evidence-based decision-making tools, explainable machine learning, and data processing methods for medical research, environmental studies, and complex human-machine applications.
- Horizon 2020, SARAS (Smart Autonomous Robotic Assistant Surgeon), ICT-27-2017. Postdoctoral Researcher in Deep Learning for Activity Recognition within the Visual Artificial Intelligence Laboratory (Aug 09 2019 - Sept 30 2021).
- Horizon 2020, RESPONSE (integRatEd Solutions for POsitive eNergy and reSilient CitiEs), LC-SC3-SCC-1-2018-2019-2020.
- Horizon 2020, SPEAR (Secure and PrivatE smArt gRid), SwafS-09-2018-2019-2020.