Konferenzen  >  Informatik  >  Wissenschaftliches Rechnen und Datenwissenschaft

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

Faithful data representation is key. While this is universally true for visual analysis, the field of biological data communication has its unique challenges and open questions. Researchers need the right context to interpret data accurately, especially when uncertainties arise from factors like sampling choices or analysis parameters. Simplifying data for wider audiences must still convey its complexity and uncertainty to support informed decisions. This Dagstuhl Seminar will bring together experts in data visualisation and design, researchers, public educators, and journalists to explore methods for embracing and communicating biodata complexity and uncertainty.

Mulitimedia und Computergrafik, Spiele,    Benutzerschnittstellen, User Experience, Virtuelle Realität

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;     Tel.: [+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

Neuronale Netze und Künstliche Intelligenz, Maschinelles Lernen,    Mustererkennung und Bildverarbeitung, Maschinelles Sehen

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.

Numerische Analysis,    Neuronale Netze und Künstliche Intelligenz, Maschinelles Lernen

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,    Computerphysik und Numerische Simulation

Marmara University, Department of Mathematics

2nd International Conference on Mathematics and Computers with Applications (MCWA) is a hybrid scientific conference to be held from July 21 to July 23, 2026 in Istanbul, Türkiye with both online participation via Zoom and face-to-face sessions, bringing together researchers, students, and practitioners working in mathematical sciences, computer science and their applications across various disciplines to present research results, exchange ideas and foster collaboration, with contributions covering theoretical developments and practical work in pure and applied mathematics and computing.

MCWA-2026 Organizing Committee Secretariat;     Email: icomistanbul@gmail.com

Mathematical sciences, computer sciences and their applications in the all scientific disciplines

Allgemeine wissenschaftliche Mathematik und fachübergreifende Veranstaltungen,    Angewandte Mathematik (allgem.)

National Institute for Research and Development of Isotopic and Molecular Technologies INCDTIM Cluj-Napoca

The ICASC 2026 conference continues the series of the former 16 annual events of the Romanian LCG Federation (RO-LCG) on “Grid, Cloud and High-Performance Computing in Science“ (2007-2022). Its title has been changed and the topics have been expanded to offer a more comprehensive coverage of the current evolution in scientific computing.

Event Secretary;     Email: icasc@itim-cj.ro

List of Topics: T1 — Advanced Computing Infrastructures & Architectures T2 — Scientific Software, Workflows & Automation T3 — Data Management, Big Data & Analytics T4 — Artificial Intelligence & Intelligent Computing T5 — Modeling, Simulation & Digital Engineering T6 — Communication Systems, IoT & Edge Computing T7 — Engineering Systems, Security & Industrial Applications

Institute for Computational and Experimental Research in Mathematics (ICERM)

The goal of this workshop is to deepen connections between algebraic geometry and data science. Behind many optimization methods is the modeling assumption that data lie on, or close to, an algebraic variety. We will discuss methods to sample from varieties or distributions centered on them, extending the methods to adaptive techniques and for sampling from level sets. We will investigate consequences and applications of these methods for computations in Bayesian statistics, likelihood inference, and topological data analysis. A complementary area of focus will be on learning functions and varieties from samples, and its uses to test goodness of fit, to investigate the geometric and topological structure of data, and for structured matrix and tensor decompositions. The workshop is at the interface of applied algebraic geometry with its applications in numerical computations, machine learning, and statistics. It will bring researchers from these communities together to learn from each other and exchange ideas.

Tel.: [4018635030];     Email: info@icerm.brown.edu

Geometrie und Topologie,    Algebra

Wilhelm and Else Heraeus-Foundation

The purpose of this seminar is to bring together young and experienced researchers in the rapidly developing field of neutral-atom quantum information processing, and to give them the opportunity to interact and develop new ideas in a pleasant scientific environment. We will target and discuss the latest developments and major challenges on the way to controlling large-scale quantum systems.