Conferences  >  Informatics  >  Human-Computer Interaction, User Experience, Virtual Reality

University of Cambridge

We are pleased to invite you to the 3rd Workshop on Low-Cost Digital Solutions for Industrial Automation, hosted at the Institute for Manufacturing, University of Cambridge. This workshop aims to foster innovation in low-cost digitalization and digital transformation by showcasing new concepts, methods, and technologies that empower Small and Medium-Sized Enterprises (SMEs) across sectors such as manufacturing, construction, logistics, and healthcare. This year’s theme, “Low-Cost Technologies Driving Sustainability,” specifically encourages submissions exploring how accessible digital solutions can support sustainable practices. We also welcome broader contributions in areas such as system design, supply chain, industrial applications, legacy systems, and security.

Phone: [07958136759];     Email: sjb351@cam.ac.uk

Digital technologies, healthcare, construction, manufacturing, agriculture, digital transformation, sustainability, design, control, low-cost, SMEs, supply chains, logistics, industry, internet of things, smart factory, systems

Engineering & Industry (general),    Internet of Things (IoT) and Sensor Networks

Navigating Frontiers: Smart Systems for a dynamic World

Optica

Join our online industry meeting dedicated to the rapidly evolving field of Extended Reality (XR), a domain poised to transform everyday life and societal interactions. This event offers a prime opportunity for companies in photonics and optics to tap into expansive business prospects. As XR technology broadens into more applications, the demand for innovative solutions, particularly in headset design, is soaring. Key development areas include reducing headset weight and cost while improving visual metrics such as field of view, frame rate, and latency. This meeting will be especially valuable for companies specializing in optics and photonics, focusing on the critical components that are driving the next generation of XR technology. We will delve into advancements in near-eye displays, waveguides, eye-tracking, and sensing systems. Participants will gain insights into specific needs and emerging trends within the XR industry, positioning themselves at the forefront of this dynamic field.

SEIT Lab, Department of Computer Science, University of Cyprus

Phone: [+35722892693];     Email: george@ucy.ac.cy

Human-centered AI methods, approaches, and systems • Explainable AI methods • Democratization of AI • Persuasive technologies in IUI • Privacy and security of IUI • Knowledge-based approaches to user interface design and generation • User modelling for intelligent interfaces • User-adaptive interaction and personalization • IUI for crowd computing and human computation • Human control in daily automations • Trust and reliance in intelligent systems Computational innovation • Interactive machine learning • Human-in-the loop AI testing and debugging • Human-centered recommendation and recommender systems • Generative models • Human-in-the-loop reinforcement learning • Intelligent user interfaces for generative AI Innovative User Interfaces • Affective interfaces • Intelligent aesthetic interfaces • Intelligent collaborative interfaces • Intelligent AR/VR interfaces • Intelligent visualization and visual analytics • Intelligent wearable and mobile interfaces • Intelligent tangible interfaces Intelligent Multimodal Systems • Embodied agents • Multimodal AI assistants • Intelligent multimodal interfaces Intelligent Applications • Education and learning-related technologies • Healthcare and wellbeing • Automotive • Assistive technologies • Entertainment • Workplace happiness • Social media • Internet of Things (IoT) • Smart homes Large Language Models and Agentic AI • End-user interaction with LLMs, agents, and multimodal models (e.g., chatbots, image generation) • LLMs and agents in the workplace • Human-agent interaction and multi-agent systems • Bias in LLMs and agents • The effects of LLMs and agents use on creative tasks • Personalized user interaction with LLMs and agents • Prompt engineering • User control and steering of LLMs and agents (e.g., RLHF, chaining, instruction tuning) Evaluations of Intelligent User Interfaces • User experiments and studies • Reproducibility (including benchmarks, datasets, and challenges) • Meta-analysis • Mixed-methods evaluations