Meetings/Workshops on Applied Mathematics (in general) in the United States (USA)

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DS17 — SIAM Conference on Applications of Dynamical Systems
21 May 2017 - 25 May 2017 • Snowbird, Utah, United States
Workshop III: Data Assimilation, Uncertainty Reduction, and Optimization for Subsurface Flow
22 May 2017 - 26 May 2017 • Institute for Pure and Applied Mathematics (IPAM),, United States
There are major computational challenges and substantial uncertainties associated with model inversion and performance optimization in oil field applications. As production and (in some cases) 4D seismic and electromagnetic data are collected, there are inevitably discrepancies between the predicted and actual reservoir responses. This drives the need for data assimilation, usually referred to as history matching in petroleum engineering. History matching involves the solution of a computationally demanding, highly ill-conditioned, inverse problem. Key complications that arise are the uncertain nature of the geology (and thus the need to "properly" sample the posterior distribution), combined with the need to retain geological realism in history-matched reservoir descriptions. Additional complexity enters as a result of the unknown rock-physics quantities needed to integrate multiphysics data sets. Applications received by Monday, March 27, 2017, will receive fullest consideration.
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Transforming Analytical Learning in the Era of Big Data
05 Jun 2017 - 14 Jul 2017 • The University of Michigan School of Public Health, United States
This full-time 6-week summer institute will introduce undergraduate students to emerging challenges at the intersection of Big Data, Statistics, and Human Health. Lectures will be led by a diverse group of stellar biostatistics, statistics, electrical engineering, and computer science faculty at the University of Michigan. Working in teams, students will participate in mentored big data research projects. A stipend is available for successful applicants.
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AIM workshop — Phase transitions in randomized computational problems
12 Jun 2017 - 16 Jun 2017 • American Institute of Mathematics, San Jose, Calif, United States
This workshop, sponsored by AIM and the NSF, will be devoted to the study of random constraint satisfaction problems (CSPs), with an emphasis on threshold phenomena and related algorithmic challenges. Heuristic methods of statistical physics predict a rich phase diagram for many problems of this type. In recent years, building on the physics insight, some of these predictions have been rigorously proved.
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Math-to-Industry Boot Camp II
19 Jun 2017 - 28 Jul 2017 • University of Minnesota, Minneapolis, United States
The Math-to-Industry Boot Camp is an intense six-week session designed to provide graduate students with training and experience that is valuable for employment outside of academia. The program is targeted at PhD students in pure and applied mathematics. The boot camp consists of courses in the basics of programming, data analysis, and mathematical modeling. Students will work in teams on projects and will be provided with soft skills training. There will be two group projects during the session: a small-scale project designed to introduce the concept of solving open-ended problems and working in teams, and a "capstone project" that will be posed by industry scientists. The students will be able to interact with industry participants at various points in the program. Applicants must be current graduate students in a PhD program at a US institution during the period of the boot camp.
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Conference on Classical and Geophysical Fluid Dynamics: Modeling, Reduction, and Simulation
26 Jun 2017 - 28 Jun 2017 • Virginia Tech, Blacksburg, Virginia, United States
This conference will bring together applied mathematicians at various stages of their careers as well as leading engineers and geophysicists. The goal is to exchange experiences and ideas necessary for the development of novel strategies to tackle challenging turbulent flows arising in engineering and geophysical fluid dynamics. These strategies will include effective analytic and data-driven dimension reduction that is essential for the mathematical modeling and numerical simulation of these turbulent flows. A partial list of topics that we intend to cover at the conference includes: modeling of turbulent flows in climate and engineering applications, state-of-the-art reduced order modeling techniques and stochastic parameterization techniques, the associated numerical implementations, and usage in different contexts such as flow control, instabilities, bifurcation analysis and transition to turbulence, predictability and prediction, and uncertainty quantification.
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Enumerative Geometry, Mirror Symmetry, and Physics
17 Jul 2017 - 21 Jul 2017 • Champaign-Urbana, IL, United States
Conference on Enumerative Geometry, Mirror Symmetry, and Physics , at the University of Illinois at Urbana-Champaign.
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Introductory Workshop: Phenomena in High Dimensions
21 Aug 2017 • Mathematical Sciences Research Institute, Berkeley, United States
This workshop will consist of several short courses related to high dimensional convex geometry, high dimensional probability, and applications in data science. The lectures will be accessible for graduate students.
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Topical Workshop: Pedestrian Dynamics: Modeling, Validation, and Calibration
21 Aug 2017 - 25 Aug 2017 • ICERM/Brown University, Providence, RI, United States
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 1950s 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. The main aim of this workshop is to initiate contact between a variety of scientific fields,to foster interdisciplinary research and to explore new research directions such as data assimilation techniques and big-data analysis.
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Complex High-Dimensional Energy Landscapes
11 Sep 2017 - 15 Dec 2017 • Institute for Pure and Applied Mathematics (IPAM),, United States
Recent advances in computational resources and the development of high-throughput frameworks enable the efficient sampling of complicated multivariate functions such as energy and electronic property landscapes of inorganic, organic, biomolecular, and hybrid materials, and functional nanostructures. Combined with the recent focus on data science and the materials genome initiative, this leads to a rapidly growing need for numerical methods and a fundamental mathematical understanding of efficient sampling approaches, optimization techniques, hierarchical surrogate models and coarse graining techniques, and methods for uncertainty quantification. The goal of this long program is to bring together the scientific communities from pure and applied mathematics with computer science, materials science, chemistry, physics, and biomolecular science to advance the understanding of simulation, stochastic sampling and optimization methods for multidimensional energy landscapes.
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ICERM Semester Workshop: Waves and Imaging in Random Media
25 Sep 2017 - 29 Sep 2017 • Providence, United States
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 media, e.g. metamaterials
Wave propagation and imaging, applied mathematics, hyperbolic, differential equations, probability theory, statistics, optimization, numerical analysis, radar and seismic reconstruction, laser beam, light propagation, source and reflector imaging, sensor arrays, matrix theory, metamaterials
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ICERM Semester Workshop: Mathematical and Computational Aspects of Radar Imaging
16 Oct 2017 - 20 Oct 2017 • Providence, United States
This workshop will bring together mathematicians and radar practitioners to address a variety of issues at the forefront of mathematical and computational research in radar imaging. Some of the topics planned include shadow analysis and exploitation, interferometry, polarimetry, micro-Doppler analysis, through-the-wall imaging, noise radar, compressive sensing, inverse synthetic-aperture radar, moving target identification, quantum radar, multi-sensor radar systems, waveform design, synthetic-aperture radiometry, passive sensing, tracking, automatic target recognition, over-the-horizon radar, ground-penetrating radar, and Fourier integral operators in radar imaging.
Radar practitioners, radar imaging, shadow analysis, interferometry, polarimetry, micro-Doppler analysis, through-the-wall-imaging, noise radar, compressive sensing, inverse synthetic-aperture radar, moving target identification, quantum radar, multi-sensor radar systems, waveform design, synthetic-aperture radiometry, passive sensing, automatic target recognition
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ICERM Semester Workshop: Recent Advances in Seismic Modeling and Inversion: From Analysis to Applications
06 Nov 2017 - 10 Nov 2017 • Providence, United States
This workshop will bring together academic and industrial researchers with the goal of addressing some of the key challenges in the analysis of seismic inverse problems, with emphases on reconstruction, big data and fast algorithms. We aim to facilitate interactions among scientists addressing all aspects of these problems, from analysts addressing such questions as stability and uniqueness through geophysicists developing new acquisition systems and applying cutting-edge ideas to field data sets. The workshop will place particular emphasis on fast algorithms that address the unique big-data requirements of seismic imaging from the reservoir to whole-Earth scale. Specific topics will include analysis of seismic inverse problems leading to reconstruction (iterative or direct) from finite data; emerging acquisition technologies; uncertainty quantification; big-data simulation; inversion and model reduction, including compressed sensing; fast solvers in frequency and time; anisotropy; and applications at a variety of scales.
seismic inverse problems, reconstruction, fast algorithms, seismic inverse problems leading to reconstruction, emerging acquisition technologies, uncertainty quantification, inversion and model reduction, fast solvers in frequency and time, anisotropy
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Memory Formation in Matter
02 Jan 2018 - 09 Mar 2018 • Santa Barbara, United States
Memory is the ability to encode, access, and erase signatures of history and typically requires broken symmetry or ergodicity. This program will develop the conceptual underpinnings for memory in materials and broader connections to science and math.
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DCC — 2018 Data Compression Conference
27 Mar 2018 - 30 Mar 2018 • Snowbird, UT, United States
The Data Compression Conference (DCC) is an international forum for current work concerning data compression and related applications. The conference addresses not only compression methods for specific types of data (text, images, video, audio, medical and scientific data, graphics, web content, etc.), but also the use of techniques from information theory and data compression in networking, communications, and storage applications involving large datasets (including image and information mining, retrieval, archiving, backup, communications, and human-computer interface). Both theoretical and experimental work is of interest.
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PMAPS — 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems
24 Jun 2018 - 28 Jun 2018 • Boise, ID, United States
The International Conference on Probabilistic Methods Applied to Power Systems cover all aspects of probabilistic and statistical modeling of power systems.
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DS19 — SIAM Conference on Applications of Dynamical Systems
19 May 2019 - 23 May 2019 • Snowbird, Utah, United States

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