Conferences  >  Informatics  >  Algorithms and Data Structures

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

Scientific Computing and Data Science,    Clinical Data Management, e-Health

Society for Industrial and Applied Mathematics (SIAM)

Applied Mathematics (in general),    Numerical Analysis and Computational Mathematics

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

Scientific Computing and Data Science,    Clinical Data Management, e-Health

International Association of Ontology and its Applications (IAOA)

08-12 September 2025 (Catania, Italy), 04-05 September 2025 (online)

Information Theory, Foundations of Computer Science,    Information & Knowledge Management, Big Data Computing

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

Constraint optimization is today a de facto practical approach to efficiently solving various types of NP-hard optimization problems arising from real-world settings. This is primarily due to significant advances in practical algorithms and implementation-level techniques, which have resulted in increasingly efficient and robust constraint optimization solvers for a range of NP-hard declarative languages. However, the need for even more efficient and robust constraint optimization solvers continues to grow, as in several contexts more and more complex optimization problems need to be solved.

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

Research in Bayesian optimisation spans multiple domains, including Machine Learning, Statistics, Engineering, and Operational Research. This makes it a multi-disciplinary field that benefits from a wide range of perspectives and methodologies, but also means the community is dispersed. As a result, there is a need for a forum where researchers from different disciplines can share insights, compare approaches, and collaborate on standardizing tools and benchmarks.

Neural Networks and Artificial Intelligence, Machine Learning,    Optimization Theory, Operational Research

entwickler.de Akademie | Software & Support Media GmbH

Kubernetes gilt als mächtig – und mitunter herausfordernd. In diesem Camp lernen Sie die Grundlagen verständlich und praxisnah kennen. Dank einer steilen Lernkurve bewegen Sie sich schnell sicher in der Kubernetes-Welt und sprechen bald die Sprache der Profis. Auf einem eigenen Cluster mit drei Knoten üben Sie Ressourcennutzung, Deployment und Monitoring – unterstützt durch einsteigerfreundliche Tipps, Tools und Best Practices für einen sicheren Betrieb. In drei intensiven Tagen steigen Sie zunächst mit einer verständlichen Einführung in die grundlegenden Konzepte von Kubernetes ein. Dazu gehören ein Überblick über die Plattform, zentrale Begrifflichkeiten sowie erste praktische Schritte wie das Arbeiten mit Namespaces, Deployments und Upgrades. Anschließend widmen Sie sich den essenziellen Bausteinen: Sie lernen, wie Pods – die kleinste Recheneinheit in Kubernetes – funktionieren, wie Health Checks und Scheduling durchgeführt werden und wie Deployments sowie ReplicaSets effizient genutzt werden. Auch Themen wie Volume Management, Services, DNS und Service Discovery sowie Rollout-Strategien und Ingress werden praxisnah behandelt. Im fortgeschrittenen Teil des Camps beschäftigen Sie sich mit der Anwendung komplexerer Funktionen, darunter Jobs und Cronjobs, das Monitoring mit Prometheus, Logging mit Elastic sowie Sicherheitsaspekte wie Role-Based Access Control (RBAC). So erhalten Sie einen umfassenden Einblick in die Arbeit mit Kubernetes – vom ersten Deployment bis zum sicheren Betrieb produktiver Anwendungen.

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

Kubernetes, Overview, Begrifflichkeiten, Namespaces, Deployments, Upgrades, Pods, Health Checks, Scheduling, ReplicaSets, DNS, ServiceDiscovery, Cronjobs, Monitoring, Logging, Security, RBAC, DevOPs

Information Security and Information Privacy,    Training in Computer Science, Courses

The Latin American Algorithms, Graphs, and Optimization Symposium (LAGOS) is a biennial event that brings together researchers and practitioners from around the world. Since 2001, LAGOS has served as a key forum for the exchange of ideas and collaboration. It is the merger of two Latin American conferences: the Brazilian Symposium on Graphs, Algorithms, and Combinatorics (GRACO) and the Latin American Conference on Combinatorics, Graphs, and Applications (LACGA).

Graph Theory and Combinatorics,    Optimization Theory, Operational Research

MIP South America is supported by the Mixed Integer Programming Society (MIPS), a section of the Mathematical Optimization Society (MOS).

The Mixed Integer Programming (MIP) Workshop is a single-track workshop highlighting the latest trends in integer programming and discrete optimization, with speakers chosen by invitation. It brings together researchers, students, and industry actors from around the globe, fostering collaboration and providing a showcase for students, early career academics, and developments in industry and novel applications. In this edition, we are putting a special focus on bringing a considerable number of speakers based in different countries of South America.

Optimization Theory, Operational Research,    Courses and Events for Math Students and Early Career Researchers

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?

Scientific Computing and Data Science,    Modeling and Simulation

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

Automated deduction is now more than half a century old. Its theoretical foundations, i.e., the notions of soundness, completeness, decidability, and complexity date back to these times or even earlier. In the last couple of decades though, due to the massive development of powerful processors with several to many cores, large, layered, and fast memories, GPUs, machine learning, cloud computing, and huge storage, the world has changed. In this new world, novel infrastructure and techniques often challenge our foundations. For instance, parallel and portfolio solvers question the once revered notion of completeness, in favor of a more vague notion of practical efficiency. Some time to assess the current status of research on deduction and its future is necessary.

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

The mathematical study of fundamental objects such as curves, embedded graphs, surfaces, and 3-manifolds has a rich and old history. However, the study of their algorithmic and combinatorial properties and the underlying computational questions is still in its infancy. There is a diverse pool of open problems and unanswered questions from the complexity- theoretic side. Examples include the hardness of realizability, the fine-grained complexity of distance and similarity measure computations, the existence of polynomial-time algorithms for flip distances, or the approximability of such distances. When dealing with polyhedral structures associated with geometric or topological objects, methods from Combinatorics and Algebra come into play to analyze structures such as associahedra, secondary polytopes, and mapping class groups of surfaces. Applied fields such as trajectory analysis and machine learning bring new questions and a fresh perspective to the field. This Dagstuhl Seminar on intractability in discrete geometry and topology will bring together researchers from the fields of computational complexity, computational geometry, topology, discrete geometry, and graph drawing; and will focus on the algorithmic, combinatorial, and computational questions mentioned above.

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

dependent randomized rounding; sampling; algorithms; statistics; economics and computation

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

In this one-week seminar, recent advances in the area of temporal graphs will be presented, discussed, and some of the current key challenges will be highlighted to better understand the many facets of the computational complexity of temporal graph problems. As this research area grows and broadens internationally, our aim is to bring together people from the various theoretical and practical sub-communities of temporal graphs in order to establish new and to strengthen existing links between these communities.

Models and Classes; Complex Network Analysis; Parameterized Complexity Analysis; Algorithm Engineering; Distributed Computing

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

analysis of algorithms; smoothed analysis; algorithms with predictions; beyond worst-case analysis; semi-random models

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

This workshop concerns cutting edge research in combinatorics and graph theory, an area central to understanding structures which appear in modern technology, such as the internet and communication devices. Problems that were previously intractable can now be approached due to advances in computing. This workshop will feature 4-6 working groups on research on topics including graph matchings and algorithms, combinatorial coding theory, graph invariants, and algebraic graph theory. Research results from the workshop will be incorporated into Sage, a free open-source computer algebra system, and Python.