Conferences  >  Mathematics  >  Optimization Theory, Operational Research

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Geometry and Topology,    Neural Networks and Artificial Intelligence, Machine Learning

University of Liverpool

This two day Colloquium aims to bring together researchers in discrete mathematics, from areas such as structural and algorithmic graph theory, extremal combinatorics, logic and foundations of Computer Science. There is a four-hour tutorial on Constraint Satisfaction Problems given by Andrei Krokhin (Durham), nine invited talks, and a session with contributed one slide pitches by junior researchers.

Constraint Satisfaction Problems, Extremal Combinatorics, Structural Graph Theory, Algorithmic Meta Theorems.

Graph Theory and Combinatorics,    Mathematical Logic and Foundations

This PhD School is part of the broader CWI Research Semester Programme on Learning Enhanced Optimization, contributing to its overarching mission of advancing cutting-edge research in theoretical computer science, operations research and beyond.

Courses and Events for Math Students and Early Career Researchers,    Neural Networks and Artificial Intelligence, Machine Learning

Open Data Science Conference

ODSC West will feature 250+ speakers, instructors, and practitioners, 2,500 of your fellow data and AI practitioners, and hands-on instruction for world-class experts in: AI Agents, GenAI, LLMs, AI Engineering, Machine Learning, Deep Learning, AgentOps, LLMOps, MLOps, Ai for Robotics, Data Engineering, RAG, Reasoning, AI Safety & Security & more. You’ll also be able to build meaningful connections with speakers and peers in a relaxed setting during our networking events like the ODSC Networking Reception, Dinner with Data Scientists, Meet the Speaker session, Book Signing sessions, and more.

Phone: [none];     Email: iryna@odsc.com

ODSCWest, AI, Data Science, LLMs, Machine Learning

Neural Networks and Artificial Intelligence, Machine Learning,    Numerical Analysis and Computational Mathematics

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,    Algorithms and Data Structures

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).

Algorithms and Data Structures,    Graph Theory and Combinatorics

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.

Modeling and Simulation,    Scientific Computing and Data Science

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.

Algorithms and Data Structures,    Courses and Events for Math Students and Early Career Researchers

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

The seminar seeks to identify the most pressing needs for quantifying uncertainty in MO problems that arise in industry, along with the most promising theoretical and methodological developments that will lead to efficient algorithms for addressing the identified needs. Toward this end, the seminar aims to bring together academic and industry experts as well as early-career researchers from different research disciplines, including Evolutionary Multiobjective Optimization, Multiple Criteria Decision Making, and Stochastic/Simulation Optimization, to discuss and propose novel ideas related to modeling, theory, and novel applications of MO under uncertainty.

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

The purpose of this Dagstuhl Seminar is to audit the current experience that exists in the field, pool it, and start to describe that experience in a way that goes beyond anecdote (although anecdotes can be useful) and moves us toward advice or recipes that actually work in practice.

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

In addition to exploring new methodologies, the workshop will address key challenges such as the explainability and interpretability of decisions, data privacy, and the practical deployment of models using contextual information. While these challenges are well-recognized in the ML community, particularly with the rise of large language models, they remain underexplored in the Operations Research community. By fostering collaboration and knowledge exchange, the workshop aims to develop scalable models, promote better benchmarking practices, and expand the applicability of contextual optimization to a wider range of real-world problems.

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

Cost-effective monitoring of large transportation networks, combined with the collection of accurate and relevant data on transport, vehicle movements, and individual mobility through various technologies, is crucial for enhancing transportation service efficiency. As we have seen in the past decade, recent technological advancements have produced an enormous volume of data, which is invaluable for understanding, planning, and managing transport networks in large cities, while also addressing the limitations imposed by road network growth. The challenge of managing, analyzing, and interpreting the information collected is considerable. The objective of this workshop is to bring together statisticians and engineers, with the specific goal to share recent advances, identify pressing problems, spark productive collaborations, and ultimately advance the state of the art by developing methods for the statistical modeling of data in the field of transportation. We will foster these interactions through four theme-focused daily workshops on the following topics: network modeling, travel behavior and choice modeling, traffic flow modeling and accident and safety analysis.

Applied Mathematics (in general),    Transportation and Logistics