Computational imaging involves the use of mathematical models and computational methods as part of imaging systems. Algorithms for image reconstruction have important applications, including in medical image analysis and imaging for the physical sciences. Classical approaches often involve solving large inverse problems using a variety of regularization methods and numerical algorithms.

Current research includes the development of new cameras and imaging methods, where the hardware system and the computational techniques used for image reconstruction are co-designed. New developments have been influenced by the introduction of novel techniques for compressed sensing and sparse reconstruction. The use of machine learning methods for designing a new generation of imaging systems has also been increasingly important.

Specific topics that will be discussed include: image reconstruction, computational photography, compressed sensing, machine learning methods, numerical optimization,... (more)

Optimization appears in many computer vision and image processing problems such as image restoration (denoising, inpainting, compressed sensing), multi-view reconstruction, shape from X, object detection, image segmentation, optical flow, matching, and network training. While there are formulations allowing for global optimal optimization, e.g. using convex objectives or exact combinatorial algorithms, many problems in computer vision and image processing require efficient approximation methods.

Optimization methods that are widely used range from graph-based techniques and convex relaxations to greedy approaches (e.g. gradient descent). Each method has different efficiency and optimality guarantees. The goal of this workshop is a broad discussion of mathematical models (objectives and constraints) and robust efficient optimization methods (exact or approximate, discrete or continuous) addressing existing issues and advancing the state of the art.

In this workshop, we will explore a number of themes in the arithmetic of abelian varieties of low dimension (typically dimension 2–4), with a focus on computational aspects. Topics will include the study of torsion points, Galois representations, endomorphism rings, Sato-Tate distributions, Mumford-Tate groups, complex and p-adic analytic aspects, L-functions, rational points, and so on. We also seek to classify and tabulate these objects, in particular to understand explicitly the underlying moduli spaces (with specified polarization, endomorphism, and torsion structure), and to find examples of abelian varieties exhibiting special behavior. Finally, we will pursue connections with related areas, including the theory of modular forms, related algebraic varieties (e.g., K3 surfaces), and special values of L-functions.

Our goal is for the workshop to bring together researchers working on abelian varieties in a number of facets to establish collaborations, develop algorithms, and... (more)

The area of encrypted search focuses on the design and cryptanalysis of practical algorithms and systems that can search on end-to-end encrypted data. With encrypted search algorithms, data can remain encrypted even in use. As such, encrypted search algorithms have a wide array of applications including in data management, healthcare, cloud computing, mobile security, blockchains, and censorship- and surveillance-resistant systems.

Designing, planning, and operating many systems is challenging due to the possibility of high-impact rare events. A motivating application is the electricity power grid, whose operation can be significantly disrupted by rare weather events such as a severe storm or a polar vortex. This workshop will explore optimization and simulation approaches to designing, planning, and operating systems impacted by such events. Stochastic optimization is one approach for optimizing such systems, in which the uncertain outcomes are modeled with random variables. Rare and high-impact events provide a challenge for stochastic optimization because it is difficult to estimate the likelihood of rare events, estimates of expected values with outcomes that have very low probability but high cost are inherently unstable, and the actual distribution of the random events is often not known. Alternatively, robust and distributionally robust optimization models attempt to identify a solution that is best in... (more)

Dehn surgery has played a central role in the development of low-dimensional topology since it was first introduced by Max Dehn in 1910. Its study has stimulated several fascinating techniques that incorporate ideas from across mathematics: hyperbolic geometry, representation varieties, combinatorics, sutured manifold theory, and Floer homology, to name a few. These tools have led to sensational progress in understanding problems about Dehn surgery and low-dimensional topology at large. Furthermore, they seem well-suited to attack the major open problems in the area, such as the Berge conjecture and the L-space conjecture.

The workshop will function as a graduate summer school. At its core, the school will feature a sequence of mini-courses delivered by a cast of leading experts and distinguished expositors. The courses will unveil Dehn surgery and this suite of techniques to the next generation of researchers in the area. The school will additionally feature guided problem sessions... (more)

The Women in Symplectic and Contact Geometry and Topology workshop (WiSCon) is a Research Collaboration Conference for Women (RCCW) in the fields of contact and symplectic geometry/topology and related areas of low-dimensional topology. The goal of this workshop is to bring together women and nonbinary researchers at various career stages in these mathematical areas to collaborate in groups on projects designed and led by female leaders in the field. See below for information regarding project leaders and topics.

The mathematical fields of symplectic and contact geometry/topology, rooted in concepts from classical physics, have experienced huge growth in the past few decades. This growth has come in many forms, including multiple flavors of homology theories, symplectic embedding problems, techniques for regularizing spaces of pseudoholomorphic curves, and examples of mirror symmetry, to name a few. This workshop aims to generate research collaborations which build on the growing... (more)

WiSDM 2019 is a research collaboration workshop targeted toward women working in data science and mathematics. This program will bring together women at all stages of their careers, from graduate students to senior researchers, to collaborate on problems in data science.

Data science is typically characterized as work at the intersection of mathematics, computer science, statistics, and an application domain. The scientific focus will be on cutting-edge problems in precision health models, network analysis for gene detection, group dynamics, graph clustering, novel statistical and topological learning algorithms, tensor product decompositions, reconciliation of assurance of anonymity and privacy with utility measures for data transfer and analytics, as well as efficient and accurate completion, inference and fusion methods for large data and correlations.

Mathematical modelers face a variety of challenges, including summarizing large data sets to understand and explore a system of interest, inferring the model parameters most accurate for describing a given data set, and assessing the goodness-of-fit between data sets. Computational topology provides a lens through which these challenges may be addressed. At the same time, just as topological techniques provide opportunities for modelers, the challenges that modelers face give rise to opportunities for applied topologists. For instance, topologists may develop techniques that make model predictions based on the topology of experimental or simulation data, that analyze time-varying data, or that turn model outputs into formats suitable for machine learning.

This workshop brings together the applied mathematical modeling and applied topology communities, aiming to give modelers exposure to topological techniques still not commonly used in their community, and to give topologists exposure

The Illustrating Mathematics program brings together mathematicians, makers, and artists who share a common interest in illustrating mathematical ideas via computational tools.

The goals of the program are to:

• introduce mathematicians to new computational illustration tools to guide and inform their research;
• spark collaborations among and between mathematicians, makers and artists;
• find ways to communicate research mathematics to as wide an audience as possible.

The program includes week-long workshops in Geometry and Topology, Algebra and Number Theory, and Dynamics and Probability, as well as master courses, seminars, and an art exhibition.

Mathematical topics include: moduli spaces of geometric structures, hyperbolic geometry, configuration spaces, sphere eversions, apollonian packings, kleinian groups, sandpiles and tropical geometry, analytic number theory, supercharacters, complex dynamics, billiards, random walks, and Schramm–Loewner... (more)