Conférences  >  Informatique  >  Calcul scientifique et science des données

Semmelweis University Institute of Biostatistics and Network Science

Join us for the BIOMEDICAL DATA SCIENCE Summer School & Conference – two interconnected events where students receive intensive training in health data science (July 28 – August 5), followed by a scientific conference to share cutting-edge work in data-intensive biological and medical research (August 6 - 8).

Institute of Biostatistics and Network Science;     Email.: biostat@semmelweis.hu

Machine learning and AI applications in biomedical research Multi-omics data integration and analysis Medical imaging and computer vision in healthcare Natural language processing for clinical and biomedical texts Explainable AI and trustworthy machine learning in medicine Computational modeling of biological systems Wearable and sensor-based health data analytics Privacy-preserving techniques for biomedical data Digital health and personalized medicine Drug discovery and biomarker identification through data science Network science tools in biomedical research Causal inference in biomedical research Biostatistical approaches for biomedical data analysis

Algorithmes et structures de données,    Gestion des données cliniques, télésanté

Semmelweis University Institute of Biostatistics and Network Science

Join us for the BIOMEDICAL DATA SCIENCE Summer School & Conference – two interconnected events where students receive intensive training in health data science (July 28 – August 5), followed by a scientific conference to share cutting-edge work in data-intensive biological and medical research (August 6 - 8).

Email.: biostat@semmelweis.hu

Machine learning and AI applications in biomedical research Multi-omics data integration and analysis Medical imaging and computer vision in healthcare Natural language processing for clinical and biomedical texts Explainable AI and trustworthy machine learning in medicine Computational modeling of biological systems Wearable and sensor-based health data analytics Privacy-preserving techniques for biomedical data Digital health and personalized medicine Drug discovery and biomarker identification through data science Network science tools in biomedical research Causal inference in biomedical research Biostatistical approaches for biomedical data analysis

Algorithmes et structures de données,    Gestion des données cliniques, télésanté

ICAS - University of Catania, Italy

IAISS 2025 is a full-immersion 5-day Summer School in Tuscany on cutting-edge advances in AI and Generative AI with lectures delivered by world-renowned experts. 

Event Secretariat;     Email.: iaiss@icas.cc

Artificial Intelligence, Generative Artificial Intelligence, Large Language Models, Foundation Models, Deep Learning, Machine Learning

Réseaux de neurones et intelligence artificielle, apprentissage automatique,    Traitement automatique des langues, Linguistique informatique

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

Currently, a paradigm shift is taking place from human interpretation of results towards machine interpretation. The long-term vision here is to automate the benchmarking process further to enable machines to automatically learn the properties of algorithms. This requires a more rigid benchmarking process with all assumptions and design decisions made explicit and accessible for machine interpretation.

Réseaux de neurones et intelligence artificielle, apprentissage automatique,    Mise en œuvre et applications de l'intelligence artificielle

South African AI Association

Back for its 8th edition, AI Expo Africa is the largest Enterprise AI trade event and conference in Africa. AI Expo Africa 2025 will run 29-31st Oct 2025 in Johannesburg South Africa at the prestigious Sandton Convention Centre, uniting 2500 decision makers, investors, buyers, suppliers, innovators, SMMEs and global brands. This year it will also be joined by the inaugural UN ITU AI4Good Impact Africa Summit focused on how AI can be used to solve the UN SDGs.

Event Manager;     Email.: enquiries@aiexpoafrica.com

Machine / Deep Learning Business Solutions RPA / Intelligent Process Automation CX / UX / Chatbots / Conversational AI Avatars / Agents / Autonomous Enterprise Platform AI / NLP / LLMs / SLMs Creative Media / Generative AI Big Data / Data Ops / Analytics Cloud / Data Centre / Storage / Super Computing ML Ops / Frameworks AI in Security & DevSecOps IoT / Mobile / Edge AI Smart Devices / Hardware Autonomous Systems / Industrial Robots AR VR / Mixed Reality / Metaverse / Web3 Training / Education & Skills Women in AI Applied University R&D AI4Good / Ethics / Privacy / Standards Regulation / Policy / Responsible AI Smart Cities / Smart Society & Smart Citizen National AI Strategies / Community Building / Investing

Mise en œuvre et applications de l'intelligence artificielle,    Réseaux de neurones et intelligence artificielle, apprentissage automatique

The International Centre for Mathematical Sciences (ICMS)

Set against the backdrop of emerging high-performance computational resources, such as the UK’s forthcoming first exascale supercomputer to be sited in Edinburgh, the workshop will focus on the development of new mathematical and algorithmic methodologies aiming to make the most of the computational power of future computer architectures in materials simulation. The workshop will stimulate research collaborations between researchers from the UK, EU and USA, and will offer the opportunity for mathematicians to learn more about the new challenges and opportunities these computational platforms will bring.

Topics to be discussed will include novel approaches to computational multi-tasking and sampling; optimisation methodologies such as numerical continuation and deflation; coarse-graining and model reduction; and the rigorous mathematical analysis of such methodologies.

Simulation,    Physique de la matière condensée et des matériaux

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

In many real-world situations, the input to an algorithm is revealed piece-meal over time, and algorithmic decisions must be taken without knowledge of future inputs. This has given rise to the field of online algorithms. Traditionally, the performance of an online algorithm is measured by comparing the quality of the solution produced by the algorithm to that of an offline optimal solution. This framework, called competitive analysis, has led to a beautiful theory of worst-case analysis for online algorithms over the last few decades. At the same time, it has also been painfully obvious that this model is overly pessimistic in many situations and leads to strong lower bounds that bucket together algorithms with significant differences in observed empirical performance. In recent years, there has been an increasing push to go beyond worst-case competitive analysis of online algorithms, and several models and frameworks have been proposed that have attracted much research activity. This Dagstuhl Seminar seeks to bring together the leaders in online algorithms research to discuss and debate these approaches, helping chart the future of online algorithms for the foreseeable future.

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

Voronoi diagrams are fundamental geometric structures that divide space into regions based on proximity to points or sites. They play an important role in many fields of science and have become cornerstones of disciplines such as computational geometry, scientific computing, and optimization.

Optimisation, recherche opérationnelle,    Simulation

OECD Nuclear Energy Agency

The NJOY Nuclear Data Processing System is a modular computer software package designed to read evaluated data in the Evaluated Nuclear Data File (ENDF) format, transform the data in various ways and output the results as libraries designed to be used in various applications.

Energie nucléaire,    Physique nucléaire

This workshop, sponsored by AIM and the NSF, will bring together researchers from across the mathematical sciences to apply a broad range of mathematical, statistical, and data science tools to study the mathematical sciences community. The workshop will include both researchers currently working in this area, as well as researchers new to the field interested in applying their expertise to this area.

Developing MetaMath as an example of using mathematical, statistical, and computational methods to investigate the mathematical sciences community itself. Catalyzing research collaborations aimed at using data to answer questions about the mathematical sciences community. Exploring the variety of mathematical, statistical, and data science techniques that can be applied to gain insight into the systems and structure of the mathematical sciences community.

Mathématiques générales et evénement multidisciplinaires,    Mathématiques appliquées (en général)

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

Key questions for the seminar include identifying which language constructs are best suited for expressing mixed precision algorithms in software and determining the specific floating-point formats required. This could provide valuable feedback to hardware developers. Additionally, the seminar should address which tools can aid in and simplify the analysis of reduced precision computing, and what tools might be necessary to evaluate the benefits of these techniques. For instance, how can algorithm developers predict and quantify the energy savings achieved through the use of reduced precision?

Algorithmes et structures de données,    Simulation

Next Business Media

After a successful inaugural edition in 2025, the Data Science Conference (DSC Next 2026) is back for its 2nd edition, scheduled to take place from March 24–26, 2026, at NH Amsterdam Zuid, Netherlands. This landmark event continues to establish itself as one of Europe’s key platforms for connecting data science, machine learning, and AI professionals from academia and industry. With a broader agenda, expanded workshops, and more international participation expected, DSC Next 2026 promises to be even more impactful, offering three full days of insight, innovation, and interaction.

Diwakar Chandra Gour, Event Manager;     Tél.: [+91 84483 67524];     Email.: diwakar@datasciencenext.com

Data Ethics and Privacy, Big Data Analytics, Machine Learning and AI Applications, Data Visualization, Natural Language Processing, Predictive Analytics, AI in Healthcare, Finance, and Industry, Data Governance and Security

Réseaux de neurones et intelligence artificielle, apprentissage automatique,    Reconnaissance de formes et traitement d'image, vision par ordinateur

The International Centre for Mathematical Sciences (ICMS)

In the last few years, an important trend has emerged for using data-driven image models, in particular encoded by neural networks. Novel families of hybrid imaging methodologies, mixing data-driven and traditional mathematical approaches (such as optimisation or sampling methods) have flourished. For instance, generative or discriminative networks such as GANS, VAEs or normalising flows, can be either used in optimisation or sampling schemes as data-driven regularisers for solving inverse problems. Similarly, denoising networks or more generally regularising networks can be incorporated into optimisation or sampling schemes leading to Plug-and-Play methods. From another perspective, unrolled optimisation approaches have been investigated to provide robust network architectures as alternative to traditional black-box end-to-end networks. All these approaches have shown a remarkable versatility and efficiency to solve inverse imaging problems.

Mathématiques numériques,    Réseaux de neurones et intelligence artificielle, apprentissage automatique

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

This workshop aims to bring together researchers from diverse fields of applied mathematics to explore the critical role of variational methods in both physical sciences and data sciences. Variational problems are fundamental in modeling natural phenomena and optimizing complex systems. This interdisciplinary workshop will focus on the latest advances in the analysis of physical problems, mathematical aspects of data science, optimization techniques, and computational mathematics, and at the same time celebrate the important contributions of Rustum Choksi at the occasion of his 60th birthday. By bringing together a diverse group of scholars, the workshop will also create a venue for new research directions, innovative solutions, and enhanced computational methods.

Simulation,    Physique numérique