Events

Computational phylogenetic methods have become essential tools for understanding the evolutionary relationships that underlie much life science research. Motivated by biological questions and insights, built on a broad spectrum of mathematical and statistical ideas and approaches, and implemented through novel and sophisticated algorithmic design, their development draws from multiple fields. Bringing together researchers spanning disciplinary perspectives and techniques, this workshop will present a diverse sample of work addressing current challenges in phylogenetics, with an eye toward future progress.

The program will explore different perspectives on uncertainty quantification, efficient simulation, and the analysis of complex stochastic systems. The topics covered will include exciting recent developments on efficient methods for approximating quasi-stationary distributions, simulation of equilibrium distributions, information divergences in sensitivity analysis of rare events, large deviations methods for efficient importance sampling, accelerated Monte Carlo via nonlinear PDE, and complex probabilistic models including reflected diffusions and high-dimensional dynamics arising in chemistry and physics.

Inverse problems are widespread in many varied fields such as medical and satellite imaging, biology, astronomy, geophysics, environmental sciences, computer vision, energy, finance, and defence. These problems are inverse in the sense that they arise from seeking to use a mathematical or physical model “backwards” to indirectly determine a quantity of interest from the effect that this quantity causes on some observed data. A main challenge resulting from using models “backwards” to measure causes from their effects is that solutions are often not well posed, i.e., not unique and/or unstable with respect to small perturbations in the data. This difficulty has stimulated an important amount of research and innovation at the interface of applied mathematics, statistics, engineering, physics, and other fields, leading to great social and economic benefit through impact on science, medicine, and engineering.

The event will especially focus on the recent connections of the Fourier transform of fractal measures, Fractal Uncertainty Principles and discretised sum-product theory appearing in these topics (mixing rates / spectral gaps, Diophantine approximation problems, quantum chaos such as scattering resonance distribution and eigenstate delocalisation in high energy) and bringing dialogue between these communities to solve some of the current challenges.

Invited Speakers: Alberto Enciso (ICMAT) Simon Chandler-Wilde (Reading) Lyonell Boulton (Heriot-Watt) Fioralba Cakoni (Rutgers) Chris Judge (Bloomington) Emily Dryden (Bucknell) Cristina Trombetti (Naples) Michael Magee (Durham) Maciej Zworski (Berkeley) Wilhelm Schlag (Yale) Public Lecture: Dmitri Vassiliev (UCL)

GAP is a series of summer schools, each devoted to a topic related to geometry and mathematical physics. Traditionally, the emphasis is on interaction between speakers and participants rather than on an intensive schedule of talks. This time there will be three mini-courses, a number of invited talks, and a poster session for young participants.

The nineteenth edition of the annual GAP (Geometry and Physics - Séminaire itinérant) conference: GAP XIX --- Rome Moduli spaces and higher structures will be held at the Department of Mathematics Guido Castelnuovo, Sapienza Università di Roma in Rome, Italy, from Monday, September 9, to Friday, September 13, 2024. The conference website and links to the previous editions are available at https://www.mat.uniroma1.it/GAP2024 Mini-course speakers: Alexey Bondal (Kavli IPMU) Alberto Cattaneo (Universität Zürich) Paolo Stellari (Università degli Studi di Milano) Invited speakers: Alberto Canonaco (Università di Pavia) Francesca Carocci (EPFL) Joana Cirici (Universitat de Barcelona) Andrea D'Agnolo (Università di Padova) Chiara Esposito (University of Salerno) Simone Gutt (Université libre de Bruxelles) Noriaki Ikeda (Ritsumeikan University) Emma Lepri (University of Glasgow) Emanuele Macrì (Université Paris-Saclay) Claudia Rella* (University of Geneva) Nicolò Sibilla (SISSA) Yukinobu Toda (Kavli IPMU) * to be confirmed Organizers: Domenico Fiorenza (Sapienza Università di Roma) Donatella Iacono (Università di Bari) Hsuan-Yi Liao (National Tsing Hua University) Marco Manetti (Sapienza Università di Roma) Mathieu Stiénon (Penn State University) Ping Xu (Penn State University) Registration and financial support: There are no attendance fees, but registration is mandatory for all participants. Please register at https://forms.gle/5z79VE3t5a1NbRNBA Financial support is available for a limited number of young participants. The deadline for support applications (registration + CV) is April 30, 2024. The scientific program of GAP XIX will include a poster session. GAP XIX is supported by "Excellence Project 2023-2027" of the Department of Mathematics Guido Castelnuovo, Sapienza Università di Roma, the National Science Foundation, and the Pennsylvania State University.

This semester program brings together mathematicians, statisticians, computer scientists, and experimental biologists to address the challenges involved in genome-scale phylogenetic inference. An overarching goal is to unite biologically-sound modeling with algorithms that can be implemented in a computationally tractable manner and that scale as both the number of species and the amount of genetic data increase. Specific topics to be investigated include: theory and practice of model-based inference for trees and networks, combinatorial and algebraic approaches for inferring phylogenies, software and algorithm development for inference and visualization, Bayesian approaches to phylogenetic inference, models for phylogenetic diversity and node dating, and methods for assessing model fit.

Join us at the forefront of innovation! The Institute of Mathematics and its Applications is proud to present the AI/ML Congress 2024—an inclusive gathering of academics, industrialists, and AI enthusiasts from diverse fields. Explore the limitless possibilities of Artificial Intelligence and Machine Learning through engaging presentations, panel discussions, and unparalleled networking opportunities.

ATSF is an international conference series organized to bring together researchers from ALL areas of Approximation Theory and Special Functions to discuss new ideas and new applications. This organization, which has been held seven times so far as mini-symposia, has grown gradually over the years and will be held for the eighth time on September 4-7, 2024, hosted by TOBB Economics and Technology University (Ankara, Türkiye). For contact: atsf2024@gmail.com