Conferences  >  Informatics  >  Implementation and Applications of Artificial Intelligence

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

This Dagstuhl Seminar addresses research gaps in the continual assessment of AI systems amid post-deployment changes in requirements, user-specific objectives, deployment environments, and the AI systems themselves.

von Karman Institute for Fluid Dynamics

Now in its 6th edition, the Hands-on Machine Learning for Fluid Dynamics course has established itself as a leading training program in the field, with over 500 participants to date from academia, research institutes, and industry. This popular one-week intensive course offers a practical and accessible introduction to machine learning techniques, specifically designed for applications in fluid dynamics.

Thermodynamics, Fluid Dynamics and Statistical Physics,    Neural Networks and Artificial Intelligence, Machine Learning

Global Insight Conferences

Join operations, transformation, data and AI leaders from leading global brands for one focused day of real-world insight, actionable frameworks and strategic clarity. Hear from 25+ expert speakers from organisations including EasyJet, Centrica, NatWest, Mars, Virgin Red, Novartis, Scania and more as they reveal how they’re embedding AI responsibly to boost efficiency, reduce costs and empower people.

Phone: [02034792299];     Email: info@aiautomationconference.com

Ethical and responsible AI strategy, Governance, compliance and regulation, Workforce transformation and upskilling, ROI and value-driven automation, Data privacy and intelligent automation, Future trends and emerging technologies

Economics, Business and Marketing,    Career, Leadership and Management

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

Recent years have seen the emergence of a number of research groups that aim to advance quantum computing and to develop a skilled quantum software workforce. A particular challenge that must be overcome for safe quantum computing at scale is the creation of robust, expressive, efficient, and tractable formal verification tools. Since there is currently no event dedicated to this pursuit, the first goal of this Dagstuhl Seminar is to bring together a dedicated community of researchers in a single venue. This will give participants an opportunity to identify and discuss the most pressing challenges and promising directions for quantum programming and verification.

entwickler.de Akademie

Tauche ein in die Welt der generativen Künstlichen Intelligenz und lerne, wie du das volle Potenzial von GenAI direkt im Frontend deiner Angular-Anwendungen nutzen kannst – ganz ohne komplexe Backend-Setups. In unserem praxisnahen Bootcamp zeigen wir dir moderne AI-Workflows wie Reasoning, RAG und Agenten verständlich und direkt anwendbar. An zwei intensiven Tagen bekommst du einen kompakten Einstieg in die Grundlagen von GenAI, lernst, wie du AI clever ins Frontend integrierst und wie du die User Experience für deine Anwendungen optimal gestaltest. Unser Ziel: Du gehst direkt fit für die praktische Umsetzung nach Hause – egal ob du AI-Neuling bist oder schon Erfahrung mit Angular hast. Das Bootcamp richtet sich an Frontend-Entwickler:innen, Webentwickler:innen, Softwarearchitekt:innen, UX-/UI-Designer:innen, Technical Leads und alle, die AI-basierte Anwendungen praxisnah und benutzerzentriert gestalten wollen. Besondere Vorkenntnisse in Künstlicher Intelligenz brauchst du nicht – Neugier und Motivation reichen völlig aus. Mehr Infos zu Inhalten, Agenda und Anmeldung findest du auf unserer Website. Schau vorbei und lass dich inspirieren!

entwickler.de Akademie;     Email: info@entwickler-akademie.de

Generative AI, Angular, Frontend-Entwicklung, AI-Integration, GenAI, RAG, Reasoning, AI-Agenten, User Experience, Webentwicklung, KI Bootcamp, Praxisworkshops, AI-Neulinge, Softwarearchitektur, UX/UI Design, Technical Leads, AI-gestützte Anwendungen, JavaScript, Frontend-Workflows, AI-Funktionen

Isaac Newton Institute for Mathematical Sciences, Cambridge

This two-day workshop on Reinforcement Learning for Science: Discovery and Automation, is a follow-up event to the Isaac Newton Institute satellite programme “Bridging Stochastic Control and Reinforcement Learning.” The workshop will bring together leading experts from academia and industry to demonstrate how tailored reinforcement learning (RL) techniques can accelerate scientific discovery and drive engineering automation. It will feature invited talks and panel discussions showcasing how RL can be effectively adapted and integrated into workflows spanning medicine, the physical sciences, robotics, and complex engineering systems. By highlighting practical applications and fostering interdisciplinary dialogue, the workshop aims to catalyze new collaborations and promote the broader adoption of RL in high-impact scientific and engineering contexts.

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

The study of clustering problems dates back several decades, and has led to the adaptation of versatile and powerful algorithm design techniques. In recent years, there has been a surge of activities in the study of clustering problems from different computational vantage points, leading to various new techniques for the development of approximation algorithms. These include new algorithm prototypes that are applicable to sublinear models, and geometric tools to deal with the challenges of high dimensionality. Each of these strands of research focuses on some challenge faced in modern applications involving massive and rapidly evolving data sets, and attempts to design clustering algorithms that overcome this challenge. This had led to a series of recent results on dynamic, online, streaming and massively parallel clustering, as well as on designing clustering algorithms whose outputs are fair, robust, and differentially private. The seminar aims to bring together researchers working on clustering problems from these divergent perspectives.

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

Neural Networks and Artificial Intelligence, Machine Learning,    Human-Computer Interaction, User Experience, Virtual Reality

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

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

AI is transforming computer security in ways that have significant potential to disrupt the effectiveness of current defensive standards. The vulnerabilities of the AI systems themselves, along with their potential use as offensive tools, introduce a new dimension to the threat modeling of computer systems. As AI models increasingly power autonomous agents, this attack surface continues to expand, giving rise to novel threats that impact both society and industry. At the same time, AI models and autonomous agents could also serve as transformative tools for developing advanced defensive techniques. The rapid pace of AI development creates significant uncertainty about what will be required to defend against AI-based attacks and how to devise autonomous cyber defenses. By reducing reliance on manual intervention and integrating with existing defense mechanisms, AI defensive systems may offer new ways to counter attacks and mitigate threats. This Dagstuhl Perspectives Workshop aims to develop a systematic understanding of how AI agents can be used in both offensive and defensive security.

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

Human-Computer Interaction (HCI) is undergoing a profound epistemological shift. For decades, the field has developed a rich repertoire of research methods informed by its interdisciplinary origins. These methods have enabled HCI researchers to explore phenomena across a wide range of domains—from desktop work environments to everyday life—with approaches that span controlled experiments, ethnographic fieldwork, and design interventions. However, the increasing integration of artificial intelligence (AI), and particularly generative AI (genAI), into both interactive systems and research workflows is disrupting the foundational assumptions behind these methods. This Dagstuhl Seminar invites participants to examine how HCI research methods must adapt in light of these developments—and what new opportunities and risks this transformation entails.

Lake Como School of Advanced Studies (LCSAS)

Neural Networks and Artificial Intelligence, Machine Learning,    Social Networks and Social Aspects of Information Technology

The 4th International Conference on Advanced Sensing and Intelligent Systems (ICASIS 2026), scheduled to take place in Hong Kong, China, from May 16 to May 18, 2026

Email: cfp@icasis.org

Advanced Sensing Technologies for Healthcare, Intelligent Sensing for Environmental Monitoring, Intelligent Data Analysis and Processing for Sensor Networks, IoT, Big Data Analytics and AI

SEIT Lab, Department of Computer Science, University of Cyprus

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

Autonomous Agents, Multiagent Systems

Banff International Research Station for Mathematical Innovation and Discovery (BIRS)

Recently a variety of state-of-the-art methods in machine learning and artificial intelligence have been developed motivated by techniques from Stein’s method, a successful tool from the field of probability theory. These methods have enabled efficient analysis of the large amounts of data being produced in several scientific fields, like neuroscience, information technology, and finance. Motivated by this success, there has been an ever increasing interest in exploring further connections between Stein’s method and machine learning. The focus of this workshop is to consolidate isolated efforts and develop a theoretically principled inferential and computational framework via Stein's method for analyzing increasingly complex models and data objects. This workshop is intended to bring together prominent and promising young and diverse researchers working on Stein’s method and machine learning, and to charter the path for future development in the field.

University of Salford

The Economic Perspective on Artificial Intelligence (EPEAI) is an international academic conference series focusing on the economic, business, and policy implications of artificial intelligence (AI). The series brings together researchers, policymakers, and practitioners to analyse how AI technologies affect firms, markets, labour, and governance. Founded in 2023 by Hochschule Ruhr West (HRW) in Mülheim an der Ruhr, Germany, the EPEAI has since expanded to include partner institutions in South Africa and the United Kingdom. It is regarded as one of the first recurring scientific formats dedicated exclusively to the economic perspective on AI.

Email: info@epe.ai

New and experimental Developments in AI, (AI-driven) Entrepreneurship and AI-driven Business Models and Strategies, AI in Business Administration and Processes e.g. Finance; Accounting; Controlling; Human Resources, Marketing, Production, Supply Chain Management, Quality and Sustainability Management. GenAI; explainable AI and Decision-making; Risk and Opportunities of AI-Agents, Ethics; Regulation and Policy of AI, Digital Transformation of Skills and Jobs, Infrastructure; Energy and Finance supply and AI Competitiveness, Micro- and Macroeconomic framework: Competition; Productivity and Markets

The Minerals, Metals & Materials Society (TMS)

The 4th World Congress on Artificial Intelligence in Materials and Manufacturing (AIM 2026) is the fourth event of its kind to focus on the role of artificial intelligence (AI) in materials science and engineering and related manufacturing processes. AIM 2026 will convene stakeholders from academia, industry, and government to address key issues and future pathways.

Metallurgy and Materials Science,    Condensed Matter Physics and Materials

The Learning Ideas Conference

Co-hosted by The Learning Ideas Conference (TLIC) and the Laboratory of New Technologies and Distance Learning, University of Ioannina, the Summer Course: “AI, Teaching, and Learning” in Ioannina, Greece brings together researchers, educators, and practitioners to explore how AI is reshaping education. Featuring Dr. David Guralnick (Kaleidoscope Learning & Columbia University) and expert faculty, the course offers hands-on activities, discussions, on-site tours, and practical insights into AI’s potential to improve learning outcomes and teaching practices. Our interdisciplinary faculty covers education, AI, cognitive science, UX design, VR/AR/XR, museum studies, and more!

The Learning Ideas Conference Team;     Phone: [+1 646-481-3510];     Email: info@learningideasconf.org

summer course, summer course in Europe, Europe summer course, summer course in Greece, teaching and learning, artificial intelligence, learning innovation, workplace learning, higher education, online learning, elearning, edtech, educational technology, instructional design, digital learning, learning experience design, AI in education, learning sciences, immersive learning, VR/AR/XR in education, gamification, museum studies, museum education cultural heritage

Education,    e-Learning, Computers in Education

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

music information retrieval; audio signal processing; deep learning; open source; user interaction and interfaces

International Telecommunication Union

Kaleidoscope 2026: AI and frontier technologies for Good is the sixteenth edition of ITU’s flagship peer-reviewed academic conference, bringing together leading voices from universities, industry, and research institutions worldwide. Kaleidoscope 2026 welcomes contributions that delve into cutting-edge research for these transformative technologies in the area of telecommunications. In particular, how Artificial Intelligence (AI), quantum technologies and others still in the research phase can facilitate the management and operation of networks.

Email: kaleidoscope@itu.int

Artificial intelligence, machine learning, embodied AI, generative AI, robotics, human-computer interaction, quantum computing, quantum networks, quantum sensing, geospatial information, geospatial AI, digital twin earth, metaverse, future mobile and wireless networks, regulation, security and privacy, education

Internet of Things (IoT) and Sensor Networks,    Quantum Information Theory and Quantum Computing

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

Energy; Critical Infrastructure; Explainable AI; Machine Learning

Institute of Mathematics & its Applications (IMA)

AI Unlocked 2026, will bring together the brightest minds from academia, industry, and government to explore the power, promise and purpose of artificial intelligence. This two-day congress, chaired by Dr. Anjulika Salhan, a global expert in AI-driven innovation and founder of Systems Holdings, will be held at the prestigious Hyatt Regency in Birmingham. We invite you to join a dynamic community of AI pioneers shaping the future of machine learning and intelligent systems. World-class speakers from across sectors will share their research, breakthroughs, and real-world applications of AI, ranging from deep learning architectures and causal models to AI in finance, healthcare, governance, and regulation.

IEEE

IEEE International Conference on AI and Security for Industrial IoT Systems (AI-SIIS 2026) is a global conference that brings together scientists, engineers, industry leaders, and policymakers to explore the latest innovations in artificial intelligence and industrial electronics related technologies. It is in collaboration with KL University and IEEE SB KLEF. It is technically sponsored by IEEE IES (Industrial Electronics Society). It is a premier event bringing together experts, researchers, engineers, and industry leaders to explore the intersection of Artificial Intelligence (AI), cybersecurity, and the rapidly evolving field of Industrial Internet of Things (IIoT). The conference will address key challenges and innovations in securing IIoT systems, leveraging AI to enhance the resilience, autonomy, and safety of industrial environments.

Information Security and Information Privacy,    Internet of Things (IoT) and Sensor Networks

Banff International Research Station for Mathematical Innovation and Discovery (BIRS)

Representation learning is at the heart of a paradigm shift in machine learning, driving many of today’s most advanced artificial intelligence (AI) systems. Representation learning transforms raw data into meaningful features that machines can use to perform a wide range of tasks, such as image recognition, content recommendation, and text generation. However, a key challenge remains: ensuring that these representations are identifiable, a property that is fundamental to reliably deploying AI systems in real-world applications. Although identifiability is critical to developing trustworthy AI systems, the current mathematical understanding of representation learning in general, and identifiability in particular, is extremely limited. To address this gap in understanding, Banff International Research Station will host a workshop focusing on principled approaches for learning identifiable representations and understanding the properties of such representations.

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH