Themes

The main motto of the 2024 International Conference of the Society for Design and Process Science spans a broad spectrum of topics, focusing on AI and Generative AI technologies and their application in design and process science.

In this instance we have the opportunity to debate misconceptions about the power, suitability, success and fear in using the technology across industries and therefore Track 1 would, amongst other issues of misconceptions of using AI/GenAI search for the way of harnessing the power of formal AI/GenAI Design and Process to accelerate Science, Business and Engineering.

Knowing that the unexpected outcome and success of GenAI technologies, dependent on the widely accepted transformers architecture, is based on language models, our Task 2 looks at the challenges in this field. We would be interested in debating proficiency, linguistic transformation, and the lack of semantic interpretation of text interpretation, which affects the application of GenAI in general.

The spread of AI technologies has also made their acceptance in applied science very vocal. Track 3 describes a few, out of many possibilities, where AI/GenAI is used in resolving problems in applied science and may have an impact on scientific processes and research.

Creating operating environments where we can run AI/GenAI solutions would require the definition of computational platforms and environments in which they co-habit with a spectrum of applications of AI. Track 4 offers synergy of both: technology platforms and applications of Ai/GenAI which bring solutions across problem domains.

It remains to be seen how far we can go in using the current format of AI/GenAI technologies in design and process science and we hope that the conference would highlight “what the future holds”. What we expect from design and process science in the light of massive content generation and manipulation across disciplines.

The GenAI4DPS Conference Themes are the following (but not limited to)

  1. Track 1: Misconceptions of Using AI/GenAI in Design and Process Science
    • Understanding the lack of understanding immature designs, processes, research and engineering, underpinned with AI
    • Analysing fear of unknown AI/GenAI technologies
    • Debating ambiguity and disguised complexities of applying AI/GenAI
    • Mitigating fear, ambiguity, understanding and complexity of AI/GenAI in critical environments such as medical, financial and cyber defence
    • Avoiding irreparable harm or damage emerging from employing substantially increased levels of AI/GenAI and envisaging penetrative AI
    • Advances in AI/GenAI in automation and autonomy
    • Qualitatively harnessing the power of formal AI/GenAI Design and Process to accelerate Science, Business and Engineering
    • Exposing gaps in formal AI/GenAI design and process education.
  2. Track 2: Challenges in Generative AI and Language Models
    • Mastering natural language processing tasks with GenAI
    • Proficiency of GenAI/LLM in text generation/categorisation/translation, linguistic manipulation, sentiment analysis, and managing conversation
    • Text classification research trends: the impact of AI solutions
    • LLM as a mechanism for anomaly detection on time series data
    • Challenges in GenAI based on diminishing returns of LLM, credibility and reasoning deficit, difficulties in managing text semantics and semantic overlapping
    • Dealing with the lack of access to any external reality and criteria of truth
    • Assessing the power of prompts and their adversarial effects
    • The future of small language models
  3. Track 3: AI and Applied Science
    • Scientific discoveries from data using AI
    • Convergence of scientific data and AI technologies
    • AI ready scientific data
    • Specific nature of AI algorithms and predictive inference upon scientific data
    • Differential equations/math solved with AI
    • Physics informed machine learning for addressing dynamics of multiphysics, multiscale systems, power systems, fluid dynamics
    • Computer vision for applied sciences
    • AI/Gen AI for material science, scientific processes and research
    • AI for potential discovery of drugs and medical treatments
  4. Track 4: AI/GenAI Applications and Computational Platforms
    • Creating interactive environments for utilising data analysis and AI
    • Examining the power of clouds, fog/dust, container management, orchestration, clusters and computing edge when using AI technologies
    • Controlling infrastructure and computational power in performing complex AI/GenAI solution
    • Correlation between simulation and deep generative models, valuable for problem solving, creativity and research
    • Intelligent computational edge and AI algorithms
    • Applications of AI/GenAI in climate change, environmental science, sustainable building, engineering, smart transportation, governance and exercising democracy
    • Applying Ai/GenAI when supporting public and personal health, mental health, addressing challenges in sports injury prevention and rehabilitation, supporting social and elderly care
    • AI powered devices in medicine, healthcare delivery, continuous, lifelong and autonomous learning