Programs & Events
Algorithmic advances and Implementation Challenges: Developing Practical Tools for Phylogenetic Inference
Nov 18 - 22, 2024
Inferring phylogenetic relationships requires complex mathematical models. As advances are made in modeling complex evolutionary processes, we need practical algorithms that translate the mathematical advances into software tools. This translation of theory to usable tools is more challenging than it may appear. Phylogenetic problems are often NP-hard, necessitating heuristic solutions that can compromise accuracy. The accuracy and scalability of such heuristics are often established only empirically, creating a need for careful simulation and testing. Moreover, software tools are used within complicated pipelines, so the input to tools may be impacted by errors from prior data processing steps. In addition, the output has many aspects, from the discrete-spaced topology to continuous-spaced branch lengths and other numeric parameters, and measures of uncertainty and visualizations. Furthermore, software tools need to be evolvable, allowing the incorporation of new features and new... (more)
Organizing Committee
- Barbara Holland
- Simone Linz
- Siavash Mirarab
- Erin Molloy
Harmonic Analysis and Convexity
Dec 9 - 13, 2024
In recent years, there has been a significant increase in the interaction between harmonic analysis and convex geometry, leading to solutions for several longstanding open problems, discovery of new phenomena, as well as many new intriguing open questions. These connections were studied during the Fall 2022 ICERM semester on “Harmonic Analysis and Convexity”. The objective of this workshop is to revisit and review the results produced during the semester and the subsequent year.
The primary areas of focus for the workshop will encompass: The Fourier approach to Geometric Tomography; Volume and Duality; Bellman technique for extremal problems in harmonic analysis; Convexity of solutions to Hamilton–Jacobi–Bellman equations; as well as numerical computations and computer-assisted proofs: Exploring the use of computational methods for theoretical aspects, including optimal algorithms, as well as practical implementation.
Organizing Committee
- Javier Gomez Serrano
- Irina Holmes Fay
- Alexander Koldobskiy
- Sergei Treil
- Alexander Volberg
- Artem Zvavitch
Computational Learning for Model Reduction
Jan 6 - 10, 2025
Reduced order modeling (ROM) has become an important tool in computational science for accelerating model-based simulations, including those governed by parametrized differential equations. Through the approximation of high-dimensional features with low-dimensional representations, ROM consists of proven strategies that build accurate emulators for the field or response of computationally expensive high-fidelity models using only a fraction of the simulation cost. In forward prediction or outer loop design and optimization, ROM has the potential to substantially improve the efficiency of current simulation-based techniques.
While ROM has seen considerable success in numerous applications, they continue to attract active research and development. This workshop showcases emerging frontiers in ROM by bringing together researchers whose core interests lie in model reduction and approximation theory, but who have also explored and developed novel methods that utilize various aspects
Organizing Committee
- Yanlai Chen
- Sigal Gottlieb
- Serkan Gugercin
- Fengyan Li
- Akil Narayan
Women in Mathematical Computational Biology
Jan 13 - 17, 2025
Biological systems are typically highly interconnected and complex. With technological advances, it is possible to collect massive amounts of data from these systems, but it is not always clear how to organize the information to draw conclusions and make predictions. In such cases, mathematical formulations are powerful tools allowing researchers to frame questions, explore patterns, and synthesize information. Augmenting and expanding computational algorithms, machine learning algorithms, and data science techniques is necessary to keep pace with the complexity of the models needed for predictive modeling. The interdisciplinary nature of mathematical biology requires a variety of skills and facilitating interaction among research groups and institutions is important to moving the discipline forward.
The workshop aims to build research collaboration among researchers in mathematical biology. Participants will spend a week making significant progress on a research project and foster... (more)
Organizing Committee
- Ashlee Ford Versypt
- Rebecca Segal
- Suzanne Sindi
Patterns, Dynamics, and Data in Complex Systems
Jan 21 - 24, 2025
The study of pattern formation in biological, ecological, physical, and social systems involves a rich interplay between theory, modeling, and computation. Analytical approaches using the theory of dynamical systems and partial differential equations have made powerful contributions to our understanding of nonlinear waves and patterns, yet many open questions remain in the study of higher-dimensional patterns and complex spatiotemporal behaviors. These analytical tools go hand-in-hand with computational methods, including numerical continuation and agent-based simulations. Together these approaches also complement empirical techniques, particularly in studies of biological pattern formation, leading to experimentally testable predictions and quantitative summaries of data.
In recent years, new opportunities have emerged for pattern detection and identification in applications using data-scientific approaches. These applications include spiral waves in cardiac dynamics, vegetation... (more)
Organizing Committee
- Paul Carter
- Veronica Ciocanel
- Stephanie Dodson
- Alexandria Volkening
Geometry of Materials, Packings and Rigid Frameworks
Jan 29 - May 2, 2025
Given an incidence structure, one may model a variety of geometric problems. This Semester Program will revolve around two fundamental examples and their applications to modern challenges in the study, analysis, and design of materials. (1) Packings and patterns of circles where the underlying combinatorics are mixed with advanced geometric concepts and strong links are made to discrete differential geometry. (2) The rigidity and flexibility of bar-joint structures where real algebraic geometry is intertwined with sparse graph theory and matroidal techniques. A prime objective of the program is to advance the applicability of these topics to fundamental applications, most notably in statistical physics and materials science.
The program will integrate diverse fields of discrete mathematics, geometry, theoretical computer science, mathematical biology, and statistical and soft matter physics. Various workshops will be designed to attract both theoretical and applied practitioners and... (more)
Organizing Committee
- Alexander Bobenko
- John Bowers
- Philip Bowers
- Robert Connelly
- Steven Gortler
- Miranda Holmes-Cerfon
- Sabetta Matsumoto
- Anthony Nixon
- Meera Sitharam
Circle packings, minimal surfaces, and discrete differential geometry
Feb 10 - 14, 2025
Coming Soon!
Organizing Committee
- Alexander Bobenko
- John Bowers
- Philip Bowers
- Steven Gortler
- Meera Sitharam
Matroids, rigidity, and algebraic statistics
Mar 17 - 21, 2025
Coming Soon!
Organizing Committee
- Robert Connelly
- Elizabeth Gross
- Tibor Jordán
- Anthony Nixon
- Shin-ichi Tanigawa
Geometry of Materials
Apr 7 - 11, 2025
Coming Soon!
Organizing Committee
- Miranda Holmes-Cerfon
- Sabetta Matsumoto
- Vanessa Robins
- Ileana Streinu
- Louis Theran
Scientific Machine Learning for Gravitational Wave Astronomy
Jun 2 - 6, 2025
The aim of this workshop is to bring together participants from computational mathematics and gravitational wave astronomy to tackle computational challenges in leveraging data-driven methods in key areas of gravitational wave data analysis in order to maximize the science output of the ongoing and upcoming observations. The areas of focus will be: (i) noise classification and detection, (ii) waveform modeling and uncertainty quantification, and (iii) source parameter and astrophysical population Bayesian inference.
The participants will develop and apply new mathematical and computational techniques including: (i) neural network classifiers for distinguishing signals from instrumental noise, (ii) generative machine learning models for simulating realizations of non-Gaussian and non-stationary stochastic processes, (iii) surrogate models including uncertainty quantification, (iv) stochastic sampling, neural posterior estimation leveraging deep neural networks with normalizing flows or... (more)
Organizing Committee
- Sarah Caudill
- Katerina Chatziioannou
- Maya Fishbach
- Brendan Keith
- Jess McIver
- Michael Puerrer
- Joshua Speagle
- Vijay Varma
Algebraic Points on Curves
Jun 23 - 27, 2025
In recent years, there has been an explosion of activity surrounding algebraic points on curves, from many different perspectives. These include the study of measures of irrationality, isolated and parametrized points, computational methods to determine algebraic points, and the arithmetic statistics of algebraic points. In this workshop, we aim to bring together researchers from these diverse perspectives, with the particular goal of developing bridges between them. The workshop will include overview talks on the various perspectives, research talks, an open problem session, and structured time for collaboration.
Organizing Committee
- Abbey Bourdon
- Robert Lemke Oliver
- Ari Shnidman
- Isabel Vogt
- David Zureick-Brown
LMFDB, Computation, and Number Theory (LuCaNT) 2025
Jul 7 - 11, 2025
This will be a one-week conference broadly focused on the topics of the LMFDB (http://lmfdb.org), mathematical databases, computation, and number theory. The conference will include invited talks, presentations by authors of papers submitted to the conference and selected by the scientific committee following peer-review, as well as time for research and collaboration. We plan to publish a proceedings volume that will include all of the accepted papers.
The field of mathematical databases has emerged as an important area of research at the intersection of computer science and mathematics. It seeks to address questions that arise when organizing, storing, and providing access to mathematical knowledge in a structured manner. These databases are intended to be easily searchable and navigable, providing researchers, educators, and students with a convenient way to access mathematical content. There are many challenges in developing and maintaining mathematical databases, ranging from
Organizing Committee
- John Jones
- Jennifer Paulhus
- Andrew Sutherland
- John Voight