The first day of the conference comprises three workshops, to be held on Tuesday 14th December. Two of the workshops are in parallel streams in the morning. Delegates will find these events to be especially valuable where there is a current need to consider the introduction of new AI technologies into their own organisations.
Delegates are free to choose any combination of sessions to attend. The programme of workshops is shown below. There is a lunch break at 13:00-14:00 and there is a 30-minute refreshment break scheduled during the morning and afternoon sessions.
Workshops organiser: Professor Adrian Hopgood, University of Portsmouth, UK.
Morning - Stream 1 (09:30 - 13:00, including a 30-minute refreshment break)
AI for Future Digital Health - Download slides (opens in new tab)
Following the success of this workshops in prior conferences, AI for Digital Health will again bring together AI practitioners representing health provider organisations, commercial enterprises with an interest in health care, and academic researchers. The workshop will encompass a number of strategic research themes including machine learning, medical diagnosis, analysis of health records and reasoning mechanisms to support decision making.
AI offers the potential to revolutionise healthcare; the potential benefits have been well reported. The need for AI skills in healthcare has been identified by governments, and named as the principal driver for personalised healthcare and as providing a potential solution to the health funding gaps. Examples where AI can benefit healthcare and wellbeing include wearable devices for monitoring individuals, more effective diagnoses, better understanding of treatments, the minimisation of clinical risks, the closure of care gaps, drug discovery and innovative preventive healthcare solutions.
Session 1, Chair: Nirmalie Wiratunga (Aberdeen Robert Gordon University)
Session 2, Chair: Vitaliy Kurlin (University of Liverpool)
Morning - Stream 2 (09:30 - 13:00, including a 30-minute refreshment break)
AI for Software Engineering & Software Engineering for AI - Download slides (opens in new tab)
Software underpins almost all aspects of our lives today and code bases grow ever bigger and more complex as developers throughout the world write and commit many new lines of code each day. To account for this ever-growing use of software and the complexity that comes with it, people have made concerted efforts over many years to evolve software development discipline. These evolutions have encompassed many areas such as introducing more expressive programming languages, promoting the use of static analysis approaches to improve code quality, and making the whole development process more efficient using increased automation.
Alongside the ever-growing size and complexity of systems, the prevalence of software in areas that would never have previously required it is becoming more common. For instance, data scientists building reasoning models from big data often want to offer their capabilities for use by others. This brings new challenges, in that such citizen developers do not always have the expertise to use these advanced best practise tools and techniques, nor do they have the time or mandate to upskill in these areas.
AI offers the possibility to unlock new potential and opportunities in the process of engineering software, while building on the best practises of today. Some examples of this include the use of AI based techniques for detecting faults in applications, how AI approaches can be used to help in testing software and how AI can be used by developers to find the best architectures for their systems. All these examples help experienced developers manage the complexity of systems, meanwhile, AI can also be used in tooling that helps citizen developers to engineer robust applications, such as low-code platforms. In essence, AI can help augment the development process, allowing both citizen and experienced developers the space to focus on their area of expertise streamlining the adoption of best-in-class software engineering principles.
In this workshop we explore the current landscape of applying AI techniques to Software Engineering problems and the prospects for the future. Alongside this, the workshop will also cover approaches applying novel software engineering techniques in the AI space. We feature presentations Software Engineering researchers who are working on applying AI to software engineering and software engineering to AI.
Afternoon (14:00 - 18:00, including a 30-minute refreshment break)
The AI-CyberSec workshop organising committee would like to invite submissions of novel theoretical and applied research in all areas where AI and cybersecurity intersect. These include the effective use of AI technologies in defensive/offensive security applications, the malicious use of AI technologies, and the improvement of the security and resilience of AI technologies.
The workshop focuses on three research areas that intersect with AI and Security: