Events

The unprecedented amount of genomic data that has become readily available presents specific challenges for the field of phylogenetic inference, which is concerned with estimating the evolutionary relationships among collections of species, populations, or sequences. This workshop focuses on statistical modeling and the scaling of phylogenetic methods. Topics will include modeling (e.g. multispecies coalescent model with extension to networks; diversification models) and inference with speed to scale to genomic datasets, consistency, and robustness using statistical, combinatorial, and algebraic approaches. This workshop will present the latest advances in these areas and serve as a forum to spark new ideas and collaborations.

This conference on applied mathematics aims to bring together various specialists in this field to present their latest research on the following topics: - Applied Mathematics in Physics, Engineering, Economics, Medicine, Biology - Algebra, Geometry, and Their Applications - Differential Equations, Dynamical Systems, and Their Applications - Numerical Analysis. It is organized by the Department of Applied Mathematics of the Faculty of Sciences, University of Craiova, Romania and it is part of the ICAMNM series started in 2016.

The 7th Mediterranean International Conference of Pure & Applied Mathematics and Related Areas (MICOPAM 2024), which is dedicated to Professor Abdelmejid BAYAD on the Occasion of his 61th Anniversary, will be held at Sherwood Dreams Resort Hotel (Ultra All Inclusive) in Antalya, TURKEY on October 26–29, 2024.

The scope of the conference is to present and discuss recent results on the intersection of spectral theory and differential equations. The list of topics includes, in particular, spectral and scattering theory for differential operators, asymptotic analysis and homogenization, operators on graph- and waveguide-like structures, Researchers working in neighboring areas are warmly welcomed.

The FIAM conference, organized by the Forum for Industrial and Applied Mathematics, serves as a premier platform for academia, researchers, and professionals to exchange insights and innovations in the field of mathematical sciences. Through national and international gatherings, FIAM fosters collaboration, showcasing advancements in data analysis, numerical methods, and simulation techniques. With a focus on real-world problem-solving, the conference bridges theory and practice, facilitating dialogue between academia and industry. By uniting diverse perspectives and expertise, FIAM conferences propel research forward, driving solutions to complex industrial challenges and advancing the frontiers of applied mathematics.

In this workshop, we will consider challenges and best practices in translating theory to software for phylogenetic inference. We will discuss strategies adopted by the tool development community, their relative advantages, and lessons learned through software development. We will discuss a variety of objective functions (parametric and non-parametric) and algorithmic techniques used by inference methods. We will cover parallelization and how it interacts with the choice of objective function and algorithmic technique. Finally, we will discuss best practices for evaluating new and existing software tools, not just to validate the implementation but also to study accuracy and scalability in relation to theory and usage in realistic bioinformatics pipelines. In addition to discussing how theory influences tools, we will examine how tool development can inform the theoretical questions asked.

This seminar will provide an overview of the recent developments and new horizons of the burgeoning field found at the intersection of control theory and machine learning. This perspective, in which deep neural networks are viewed as controlled flow maps, has shown to be fruitful in analyzing a myriad of problems of interest in machine learning, including interpolation and generalization properties of deep neural networks, or normalizing flows for generative modeling, as well as clustering properties for Transformers – to name a few. The week-long seminar will address the topic from different points of view taking in particular recent developments in machine learning into account. Deadline for application: 1 September 2024