On financial markets one never observes the same data twice; market configurations are subject to change across time. This poses some specific challenges to inference, prediction, and optimal control in financial contexts. Classically, strong model assumptions are needed, while current research aims at methods which are robust with respect to model misspecification. This issue lies at the heart of the envisaged workshops, and the program of the workshops will reflect recent developments in this direction.

The last decade saw a rise of robust methods in probability and finance resulting in new numerical and theoretical challenges. Interestingly, these challenges bring together methodologies from PDEs, probability, stochastic analysis, and control theory. Mathematically speaking, robustness typically translates into nonlinearity showing up as a defining feature. Examples in this direction are nonlinear expectations, nonlinear PDEs, and H-infinity optimal stochastic control. Finance has... (more)

Imagine spending eight-weeks on the beautiful Brown University campus in historic Providence, RI, working in a small team setting to solve mathematical research problems developed by faculty experts in their fields.

Imagine creating career-building connections between peers, near peers (graduate students and postdocs), and academic professionals.

Imagine spending your summer in a fun, memorable, and intellectually stimulating environment.

Now, imagine having this experience with support for travel within the U.S., room and board paid, plus a $3,000 stipend*.

The 2017 Summer@ICERM program is designed for a select group of 16-20 undergraduate scholars. The program will give undergraduates an opportunity for exposure and research in the methods of “Applied Topology” in... (more)

This workshop, a formal collaboration between ICERM and the American Institute of Mathematics (AIM), is one in a series of annual REUF workshops. These workshops bring together leading research mathematicians and faculty at primarily undergraduate institutions to investigate open questions in the mathematical sciences and to equip participants with tools to engage in research with undergraduate students. This will also be a research renewal opportunity for faculty who want to re-engage in research or faculty considering a change in research area.

The goals of the workshop are to promote undergraduate research and to forge research collaborations among the participating faculty. The majority of the workshop will be spent working on problems in small research groups, reporting on progress, and formulating plans for future work. Note that there are opportunities for participants to continue research activities beyond the workshop week.

Preference will be given to faculty who teach or... (more)

Research Collaboration Workshop for Women in Data Science and Mathematics (WiSDM). 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. The scientific focus will be on cutting edge problems in the areas of predictive modeling, multi-scale representation and feature selection, statistical and topological learning, and related areas. Data science is a cross-disciplinary field relying on statistics, computer science and mathematics and driven by problems in many other disciplines. While data science has emerged as a prominent new field enrolls record numbers and attracts research talents from many scientific disciplines, the role of theoretical and applied mathematics has not been highly visible. Mathematics provides many structured representations that can be in the analysis of data arising from such diverse fields as geometric measure theory, classical analysis, computational... (more)

GirlsGetMath is a weeklong mathematics summer day-program for 9th and 10th grade high school girls in the Providence, RI area.

GirlsGetMath occurs in an encouraging environment that builds young women's confidence in math and science.

GirlsGetMath expands participants' understanding and knowledge of mathematics through computations and experimentations.

GirlsGetMath provides expert mathematical training and mentoring.

GirlsGetMath will become a replicable national model of mathematical outreach for high school girls, with an emphasis on mathematical experimentation.

This five-day non-residential mathematics program is open to high school girls who live in or near the greater Providence, RI area who will be entering the 10th or 11th grade in the fall of 2017.

GirlsGetMath@ICERM encourages 20-25 young... (more)

This workshop will provide a platform for researchers working on localized kernel-based methods to present and discuss their latest developments, as well as the current theoretical and practical challenges in the field. These methods, such as radial basis function-generated finite differences (RBF-FD) or RBF-generated partition of unity methods (RBF-PUM), promise to develop into general-purpose meshless techniques for the numerical solution of partial differential equations that inherit the ease of implementation of the finite difference method, and yet potentially possess a greater ability than the finite element method to fit any geometry or adapt to singularities or other features of the solution.

The numerical evidence collected in recent years by a rapidly growing community of researchers suggests that these methods combine numerical stability on irregular node layouts, high computational speed, high accuracy, easy local adaptive refinement, and excellent opportunities for... (more)

The complex dynamical behavior of large pedestrian crowds has long fascinated researchers from various scientific fields. Academic studies began in earnest in the last century, starting with empirical observations in the early 1950’s and continuing with the development of models in the field of applied physics. In more recent years, applied mathematicians have become increasingly interested in the analytical aspects and computational challenges related to simulation of existing models. With ongoing technical development, more and more data such as pedestrian trajectories and velocities have become available, leading to new questions of calibration of the mathematical models.

Since the inception of the field of study, several scientific communities have been independently working on the challenge of describing and simulating pedestrian dynamics. While mathematicians have mainly focused on the modeling and analytical aspects, physicists have developed experimental setups and methods... (more)

Inversion and imaging with waves is of fundamental importance in both radar and seismic reconstruction. Mathematics provides the key technology in both areas and, despite differing in many important respects, they have much in common in their underlying mathematical frameworks, approaches, and challenges. This semester program will focus on advancing their common mathematical and computational methodologies, as well as selected subjects distinct to each area, in the context of new challenges and opportunities that have arisen in recent years. Both theory and applications will be of interest. Participants will be drawn from academia, industry, and governmental laboratories in order to broadly address theory, applications, and their synergy.

The program will be influenced by recent developments in wave propagation and imaging, data acquisition and analysis, and high-performance computing. Driven by the ongoing need for more realistic mathematical models and simulations, recent advances... (more)

Wave propagation and imaging in complex environments is an important topic in applied mathematics with a wide range of applications, including not only radar and seismic reconstruction but also many others, such as laser beam propagation through clouds, light propagation through the atmosphere in astronomy, secure communications in scattering media, medical imaging, and nondestructive evaluation of materials. This cluster will involve contemporary topics on waves in random media. Recent progress in this area has been motivated on the one hand by a range of applications that involve partly or fully incoherent waves, such as time reversal, active-array imaging, passive imaging and hybrid imaging, and on the other hand by advances in sensor technology that have brought new and massive amounts of data.

Mathematically, the problem of waves in random media may be placed in a stochastic framework, where the complex environments are realizations of random fields and the scattering regimes are... (more)

In radar and seismic reconstruction, as in other areas of applied mathematics, interactions between academic and non-academic researchers create synergies that are vital to advancing both theory and applications. The purpose of this three-day workshop is to enrich the semester program through such interactions. It is expected that most participants will be drawn from the semester program; however, others are also welcome to participate. Applications from graduate students, postdocs, and other early-career investigators are especially encouraged.

Each of the first two days of the workshop will begin with background talks, after which experts from industrial and governmental laboratories will present "real-world" problems to workshop participants. The participants will then brainstorm possible approaches to the problems under the guidance of the experts. On the third day, designated participants will present summaries of the proposed approaches and their potential advantages and... (more)

Wave propagation and imaging in complex media is an interdisciplinary area in applied mathematics, with roots in hyperbolic partial differential equations, probability theory, statistics, optimization, and numerical analysis. It has a wide range of applications, including not only radar and seismic reconstruction but also many others, such as laser beam propagation through clouds, light propagation through the atmosphere in astronomy, secure communications in scattering media, medical imaging, and nondestructive testing of materials.

This workshop will present some of the latest advances in this area including wave propagation with time-dependent perturbations, source and reflector imaging in random media with sensor arrays, applications of random matrix theory for detection and imaging, imaging with cross correlation techniques, imaging with opportunistic or noise sources, applications of compressed sensing for imaging of sparse scenes, super-resolution in imaging, waves in novel... (more)

Radar imaging is a highly developed field that involves a rich variety of mathematical and computational areas, such as electromagnetic theory and partial differential equations, functional analysis, harmonic analysis, coding theory, Lie groups, and statistical signal processing. Still, many challenges remain. For example, more of the physics needs to be incorporated into solutions to the radar inverse problem, including physical scattering mechanisms, multiple scattering, moving objects, and corrections for propagation through random or complex media.

Recent hardware developments make it possible to collect an unprecedented amount of data, sampled at extremely high rates and often including polarimetry, and mathematical techniques are needed for fast, accurate image formation and interpretation of this data. Seismology is faced with many similar mathematical problems; this program provides an opportunity for synergistic development of both fields.

This cluster will bring together... (more)