Conference Programme can be downloaded from here! This link will be activated after October 10, 2024.
Themes and Focus Areas
Research and Scientific Contributions
AI Foundations for Invention and Inventive Design: Machine Learning and Deep Learning Applications in Design and Inventive Design; Neural Network Architectures and Approaches for Creative Processes and Inventive Solutions; Natural Language Processing in Ideation and Conceptualization; Evolutionary and Swarm Algorithms for Design Optimization and Conceptualization; Algorithmic Approaches to Innovation; Patterns of Evolution in Modern Systems; Identifying and Resolving Contradictions in Design; Hierarchies and System Mapping in Innovation
Theory of Inventive Problem Solving: Advancements in TRIZ Methodology; TRIZ and Systems Theory; Algorithmic and Heuristic Aspects of TRIZ; Evolutionary Patterns of Technological Systems; TRIZ for Predictive Innovation; TRIZ and Knowledge Management; Psychological Aspects of TRIZ; TRIZ in Complex Adaptive Systems; TRIZ and Computational Models; TRIZ for Eco-Innovation and Circular Economy; Integration of TRIZ with Other Innovation Methodologies; Case Studies in TRIZ Application; TRIZ in Academic Research and Education; TRIZ and Intellectual Property Strategies; Cultural and Organizational Aspects of TRIZ Implementation; TRIZ for Service Innovation; TRIZ and the Future of Work; TRIZ in Non-Technical Domains; TRIZ and Human Factors Engineering; Philosophical and Theoretical Foundations of TRIZ
Creativity and Idea Generation: AI Tools for Brainstorming and Mind Mapping; Generative Design Principles and Applications; AI Algorithms and Architectures Supporting Creativity; Generative and Adversarial Networks in Creative Domains
AI in Inventive Problem-Solving: Pattern Recognition for Problem Identification; AI-Driven Techniques for Root Cause Analysis; AI Tools for Innovative Solutions and Alternatives; Predictive Modeling in Inventive Scenarios
Interdisciplinary Inventive Design: Fusion of AI with Economics, Management, Arts and Humanities in Inventive Design; Bio-Inspired Design and Nature’s Algorithmic Solutions; AI in Social and Cultural Contextual Inventive Design; Synergy of AI with Behavioral Sciences in Inventive Design Thinking
Integrative Approaches in Inventive Design: Combining Classical Inventive Design Methods with AI Tools; Confluence of Heuristics with Data-Driven Solutions; Mixed-Methods Approaches for Comprehensive Problem-Solving; Case Studies: Successes and Challenges in Integrated Inventive Design
Structured Problem-Solving Methods: Analytical Techniques for Complex Problem Recognition; Root Cause Analysis and Systemic Solution Approaches; Techniques for Ideality and Benchmarking Innovation; Predictive Models for Future Challenges and Solutions
Resource-Driven Innovation: Maximizing Internal Resources for Optimal Solutions; Adaptive and Flexible Design Techniques; Environment and Context in Solution Generation; Integrating Available Resources into Design Strategies
Multi-Level System Analysis: Analyzing Sub-Systems and Super-Systems; Functional Analysis in Modern System Design; Interactions, Interfaces, and Integration in Complex Systems; Transition from Macro to Micro-Level Innovations
Trends of Evolution and Technology Forecasting: Predictive Models for Technological Progression; Evolutionary Patterns in Current Industries; Anticipating Breakthroughs and Tech Revolutions; Integration and Convergence in Future Technologies
Advanced Inventive Principles and Strategies: Guided Innovation with Systematic Principles; Strategies for Breaking Psychological Inertia in Design; Enhancing Creativity through Structured Techniques; Design and Redesign using Guided Patterns
Collaborative Platforms and Tools: AI Tools Facilitating Team-Based Inventive Design; Virtual Collaboration Platforms with Embedded AI Features; Feedback and Iteration in AI-Enhanced Collaborative Environments; Open Source vs. Proprietary AI Tools in Inventive Domains
Business and Economic Implications: The ROI of AI-Driven Design Processes; AI’s Impact on Design Job Markets; Transforming Traditional Design Industries with AI; Strategies for Integrating AI in Small and Medium Design Enterprises; Value Proposition of AI in Inventive Design; Organizational Change Management for AI Adoption in Design Teams; AI’s Role in Speeding Up Product Innovation Cycles; Market Differentiation through AI-Powered Design Solutions
Eco-Innovative Applications with AI: AI-Driven Strategies for Sustainable Design and Development; Machine Learning for Energy Efficiency and Renewable Energy Solutions; Deep Learning in Waste Reduction and Material Recycling; AI in Lifecycle Assessment and Environmental Impact Reduction
AI Foundations in Eco-Design: Neural Networks for Eco-Friendly Materials Discovery and Optimization; Evolutionary Algorithms in Eco-Design for Optimization of Natural Resource Use; Swarm Intelligence for Sustainable Urban Planning and Smart Cities
Advanced AI for Sustainable Inventive Solutions: AI Tools and Techniques for Carbon Footprint Analysis and Reduction; Predictive Analytics for Sustainable Supply Chain Management; AI-Enhanced Models for Biodiversity Conservation and Ecosystem Services; Generative AI for Innovative Eco-Friendly Product Design
Integrating AI with Inventive Problem Solving for Eco-Innovation: TRIZ Principles in Developing Circular Economy Solutions; AI and inventive design for Energy Efficiency and Renewable Energy Systems Design; Case Studies with TRIZ and AI in Eco-Innovation Projects; Algorithmic TRIZ for Predictive Environmental Impact Reduction
AI-Driven Creativity in Eco-Design: Generative Adversarial Networks (GANs) for Conceptualizing Sustainable Products; AI Tools for Brainstorming Green Technologies and Practices; AI in Ideation and Conceptualization for Environmental Sustainability
Interdisciplinary Approaches to Sustainable Inventive Design: Fusion of AI with Ecology, Environmental Science, and Sustainability Studies; Bio-Inspired AI Solutions for Sustainable Innovations; AI in Social Impact Assessment for Sustainable Project Design; Biomimicry and Biologically Inspired Design
AI in Resource-Driven Innovation for Sustainability: Maximizing Use of Renewable Resources through AI-Optimized Design; Adaptive AI Systems for Sustainable Water and Energy Use; AI in Enhancing the Environmental Sustainability of Manufacturing Processes
Uncharted Innovations in AI and Design: In recognition of the rapidly evolving landscape of AI-powered innovation and inventive design, we are pleased to introduce this special section, dedicated to pioneering research, inventive solutions, and thought-provoking ideas that transcend the predefined topics of our conference call. We invite submissions from across the spectrum of AI, design, sustainability, and beyond, to share insights that challenge conventional boundaries and propose forward-thinking solutions. Submissions can include, but are not limited to: (a) Innovative AI technologies, methodologies, or practices not explicitly covered in the conference themes, including novel approaches to machine learning, deep learning, and computational creativity; (b) Contributions that blend AI with other fields such as art, philosophy, psychology, or any novel interdisciplinary approach that offers fresh perspectives on design and innovation; (c) Insightful analyses or case studies on the societal, ethical, or cultural implications of AI in design, highlighting topics like privacy, equity, and the digital divide; (d) New ideas or projects that address sustainability in inventive ways not previously considered, including unconventional applications of AI in environmental conservation, social sustainability, and economic resilience; (e) Thought experiments, speculative designs, or visionary projects that use AI to explore future scenarios, challenge current paradigms, and envision the role of design in tomorrow’s world; (f) Reports on open-source projects, collaborative innovation models, or community-driven initiatives that leverage AI for public good, social impact, or grassroots invention.
Case Studies and Practitioners Contributions
Real-World Applications of AI in Design: Detailed case studies demonstrating the use of AI in the design process, from concept to product; Success stories of AI-driven design innovations in consumer products, architecture, automotive, and other industries.
Practical Implementations of TRIZ and AI Synergy: Examples of how TRIZ methodology has been combined with AI to solve complex design problems; Insights into the integration of TRIZ principles with machine learning and other AI technologies for inventive problem solving.
Traditional TRIZ in Action: Case studies demonstrating the application of TRIZ tools and principles in solving real-world problems; Examples of how TRIZ has been used to develop sustainable solutions and innovations that contribute to environmental protection; Case studies on TRIZ’s role in promoting circular economy principles in product design and manufacturing; Insights into the implementation of TRIZ for solving complex engineering challenges in the industrial sector; Case studies showcasing the adaptability of TRIZ principles across various disciplines and industries; Insights into managing innovation projects using TRIZ methodologies to streamline creativity and problem-solving; Case studies on the impact of TRIZ education on fostering a culture of innovation within organizations and institutions; Case studies demonstrating the use of TRIZ to resolve service industry-specific contradictions and enhance operational efficiency; Case studies on leveraging TRIZ for strategic patent circumvention and creating strong IP portfolios; Case studies on using TRIZ to address complex problems in medical research and healthcare delivery; Other applications not covered in this section.
AI-Enhanced Creativity and Product Development: Case studies showcasing the use of AI tools for enhancing creativity in product design and development; Examples of generative design in action, highlighting the collaborative process between AI and human designers.
Eco-Innovation and Sustainability Practices: Stories of how AI has been applied to eco-design and sustainable innovation projects; Practical examples of AI-driven strategies for energy efficiency, waste reduction, and circular economy solutions.
Inventive Problem-Solving in Industry: Narratives on the application of AI in identifying and solving inventive problems across various sectors; Insights into the role of AI in enhancing root cause analysis, ideation, and solution generation.
Cross-Disciplinary AI Projects: Exemplars of interdisciplinary collaboration involving AI, highlighting projects that fuse AI with economics, management, arts, humanities, and sciences; Case studies on the challenges and successes of interdisciplinary inventive design projects.
Integration of AI in Traditional Industries: Accounts of how AI technologies are being integrated into traditional design and manufacturing processes; Studies on the transformation of industries through the adoption of AI tools and methodologies.
AI Tools in Action with Collaborative Platforms and Tools: Reviews of specific AI tools and platforms that facilitate collaborative inventive design, including both open source and proprietary solutions; User experiences and feedback on the use of AI-enhanced collaborative environments in real-world projects.
Business Transformation through AI-Driven Design: Case studies on how AI-driven design processes have impacted the ROI, market differentiation, and innovation cycles of businesses; Insights from small and medium design enterprises on integrating AI into their operations.
Ethical, Societal, and Cultural Impacts of AI in Design: Discussions on the ethical considerations of using AI in design, including privacy, bias, and intellectual property issues; Examples of how AI-driven design is addressing or raising societal and cultural challenges.
Educational Initiatives and Workforce Development: Contributions detailing educational programs, workshops, and courses aimed at equipping designers with AI skills; Case studies on workforce development initiatives preparing professionals for the future of AI-integrated inventive design.
Challenges and Lessons Learned: Honest reflections on the challenges faced during the implementation of AI in inventive design projects; Lessons learned from failed projects or unexpected outcomes, providing valuable insights for future endeavors.
Cutting-Edge Applications of AI in Product Design: Innovative use of AI in fashion, electronics, automotive design, and more; Impact of AI on reducing design cycles and enhancing product functionality.
AI Transformations in Architecture and Urban Design: Examples of AI-driven solutions in smart city planning and sustainable architecture; Use of AI in enhancing urban livability and environmental resilience.
Breakthroughs in AI-Driven Medical Device Design: Case studies on the role of AI in developing new medical devices and health technologies; AI’s impact on personalized medicine and patient-centered design.
AI in Entertainment and Media: How AI technologies are shaping the future of entertainment, gaming, and digital media design; Case studies on AI-driven content creation and user experience design.
Retail and Consumer Goods Innovation through AI: AI applications in creating personalized shopping experiences and product customization; Success stories of AI in supply chain optimization and retail design.
AI Solutions in Agriculture and Food Technology: Innovative uses of AI for sustainable farming practices and food production design; Case studies on AI-driven food technology and packaging design.
AI-Enhanced Environmental Monitoring and Design: Examples of AI applications in environmental protection, monitoring, and ecological design; AI’s role in climate change mitigation strategies and conservation efforts.
Practical Implementations of AI in Manufacturing and Robotics: AI-driven innovations in manufacturing processes, automation, and robotics design; Success stories of AI in improving efficiency, safety, and customization in manufacturing.
AI in Financial Services and Fintech Design: Case studies on the application of AI in designing financial services, risk management, and fraud detection systems; AI’s impact on personalizing banking services and enhancing user experience.
AI-Driven Innovations in Education and Learning Technologies: Innovative applications of AI in educational content, platforms, and adaptive learning technologies; Case studies on AI’s role in transforming educational access and personalized learning experiences.
AI in Art, Culture, and Creative Industries: Explorations of AI’s contributions to art creation, cultural heritage preservation, and the design of creative experiences; Practical insights into the intersection of AI, creativity, and cultural expression.
AI for Public Sector Innovation and Design: Examples of AI applications in public services, government operations, and civic design; Insights into how AI is used to enhance public engagement, service delivery, and policy design.
Challenges in Scaling AI Solutions: Lessons learned from scaling AI projects, addressing technical, organizational, and market challenges; Strategies for overcoming barriers to AI adoption and achieving sustainable growth.
Sustainability and Circular Economy Driven by AI: Innovative AI approaches to promoting sustainability and circular economy principles in product design and business models; Case studies demonstrating the use of AI in achieving zero-waste goals and sustainable practices.
Future Directions and Emerging Trends: Predictions and insights from practitioners on the future of AI in design and innovation; Emerging trends and unexplored areas where AI could have a significant impact.