Meetings/Workshops on Scientific Computing and Data Science in the United States (USA)

Santa Fe Institute (SFI)

The Graduate Workshop in Computational Social Science Modeling and Complexity brings together a group of advanced Ph.D. students and a small faculty for an intensive two-week study of computational social science modeling and complexity. Participants will learn how to apply tools and approaches from complex systems and computation to questions in the social sciences, while advancing their independent research and working collaboratively with fellow participants. The Workshop convenes in-person and consists of seminars, independent research, formal and informal discussions, and a hackathon-style challenge.

Sociology,    Multidisciplinary or General Events in Informatics

Revolutionary. Disruptive. Game-changing. These terms describe the technologies that have helped us extend our research and our horizons, even in the midst of unprecedented challenges. They describe the dramatic changes that make up the current state of computer science, high performance computing, and cyberinfrastructure. This year’s theme, Revolutionary: Computing, Connections, You, acknowledges rapid shifts that have become a constant in the field of advanced computing; the PEARC community’s role in creating new, state-of-the-art methods; and our imperative, as individuals, to achieve an ethical and connected computing future.

Santa Fe Institute (SFI)

The Foundations and Applications of Humanities Analytics (FAHA) workshop is intended for humanities scholars who are in the early stages of applying quantitative and computational methods in their research. While primarily geared towards current PhD students, we welcome applications from those in both earlier and later stages of a research career. The residential, one-week workshop empowers scholars to apply computational tools in their own research and teaching. Participants must complete the FAHA online course prior to the workshop. The in-person workshop will seminars and tutorials, discussions, and the opportunity to workshop one’s research projects, with the guidance of program faculty. The small, supportive group of fellow participants provide a scholarly community with whom to learn and collaborate on novel humanities analytics projects.

Sociology,    Multidisciplinary or General Events in Informatics

Computational Physics and Numerical Simulation,    Applied Mathematics (in general)

Michigan Technological University

The primary focus of the proposed parallel-in-time workshop is to educate and inspire researchers and students in new and innovative numerical techniques for the parallel-in-time solution of large-scale evolution problems on modern supercomputing architectures, and to stimulate further studies in their analysis and applications. This workshop aligns with the National Strategic Computing Initiative (NSCI) objective: “increase coherence between technology for modeling/simulation and data analytics”. The conference will feature ten lectures by Professor Gander, an expert in parallel time integration. Using appropriate mathematical methodologies from the theory of partial differential equations in a functional analytic setting, numerical discretizations, integration techniques, and convergence analyses of these iterative methods, conference participants will be exposed to the numerical analysis of parallel-in-time methodologies and their implementations. The proposed topics include multiple shooting type methods, waveform relaxation methods, time-multigrid methods, and direct time-parallel methods. These lectures will be accessible to a wide audience from a broad range of disciplines, including mathematics, computer science and engineering.

The IEEE Nuclear and Plasma Sciences Society (NPSS) and its technical committee, Computer Applications in Nuclear and Plasma Sciences (CANPS) are pleased to announce the 23rd Real Time Conference. RT2022 is an interdisciplinary conference focusing on the latest developments in real time computing, data acquisition, transport and processing techniques in related fields including: nuclear and particle physics, nuclear fusion and plasma science, medical physics and imaging, astrophysics and space instrumentation as well as accelerators and control systems.

Plasma and Gas-discharge Physics, Nuclear Fusion,    High Performance Computing, Supercomputing, Parallel Computing

Intelignis

Organizations all throughout the world are moving towards a data-driven culture. Navigating the hurdles faced in leveraging new technologies for the same, is quite a challenge. Hence recognizing the best practices and methodologies is imperative for better decision making and dealing with uncertainties. The Business Intelligence & Analytics Summit brings together data & analytics leaders from across industries. Join us to gain critical insights & actionable takeaways and explore innovative technologies that can redefine your business strategy & culture.

Email: info@intelignis.com

Augmented Analytics with AI & ML, Connected Cloud, Centralized vs Decentralized Analytics, BI for Sales and Marketing Teams, Embedded BI Adoption, Data Governance, Using Data Analytics for a Better World, Leveraging Analytics for Better Customer Experience

The goal of this long program proposal is to bring together senior and junior applied mathematicians, physicists, chemists, materials scientists, engineers and biologists to discuss and debate on the current status and future perspectives of modern microscopy using computation, mathematics and modeling. Cryo-EM has revolutionized biology and life science (including very recently solving the 3D atomic structure of COVID-19, which has been greatly facilitating the development of the vaccines) and aberration-corrected electron optics and high brightness X-ray sources have transformed physical science imaging. The next steps in these fields will advance by orders of magnitude the temporal resolution and energy resolution, while maintaining atomic spatial resolution, in a variety of sample environments from near zero Kelvin in vacuum to temperatures of a thousand degrees in a highly corrosive atmosphere. These advances will transform research in macromolecules, materials, energy technologie

Applied Mathematics (in general),    Microscopy

Applied Mathematics (in general),    Information Theory, Foundations of Computer Science

Developing multi-dimensional electron microscopy would have transformative impact in physics, chemistry, materials science, nanoscience and other fields. Advancing the field requires integration of state-of-the-art atomic electron tomography, ptychography, 4D scanning transmission electron microscopy and spectroscopic techniques as well as powerful computational algorithms and mathematical modeling. This workshop will provide the opportunity to present and exchange ideas, share data, and introduce new tools and develop new imaging paradigms needed in a variety of fields.

Applied Mathematics (in general),    Microscopy

Our world is changing rapidly. Complex challenges are suddenly arising alongside an urgent demand for answers. Leveraging HPC, skilled minds employ innovative technologies to respond to the call — driven by data, simulating possibilities, and unlocking new solutions. By harnessing the power of HPC, the SC community is unleashing a deeper understanding of our world at an unprecedented pace.

The implementation of advanced algorithms with user-friendly software packages has made the cryo-EM method straightforward in practice. Despite these exciting advances, major challenges still remain, such as higher throughput, mapping continuous deformations, reconstruction of small macromolecules, and in sample preparation. For pleomorphic structures, cryo-electron tomography (cryo-ET) is the method of choice, but it is typically limited to lower resolution compared to cryo-EM, and it remains a daunting challenge to determine macromolecular structures in situ at high resolution. Overcoming these major challenges in cryo-EM and cryo-ET requires significant advances in sample preparation, hardware development and computational algorithms. The goal of this workshop is to bring together leading experts in cryo-EM, biologists, applied mathematicians and physicists to discuss and debate the current challenges and future perspectives of this very exciting cross-disciplinary field.

Applied Mathematics (in general),    Microscopy

The aim of this program is to foster the development of new mathematical tools and formalisms that will enable a new generation of ultra-scalable algorithms for a broad range of applications in computational materials science. Topics of interest will include strategies for scalable single-scale simulations, novel massively-parallel scale-bridging algorithms, and integration of extreme-scale computing into experimental and data science workflows. The program will bring together applied mathematicians, materials scientists, computer scientists, and method developers interested in unlocking the potential of upcoming exascale architectures through novel mathematical approaches.

UC Santa Barbara, Kavli Institute for Theoretical Physics (KITP)

This conference aims to explore the application of data-driven tools to learn about galaxy formation physics. It endeavors to maximize the gain from astrostatistics, data science, and machine learning for the galaxy formation field as a whole, by emphasizing the translation of data-driven results to physical understanding. This conference will focus on a sharing of expertise in data exploration and analysis tools, and an open discussion of how these may teach us about the physics of galaxy formation and evolution.

Institute for Pure and Applied Mathematics, UCLA.

Quantitatively predicting the properties of “real” structural materials is an extremely challenging endeavor, as macroscale properties depend on characteristics of the material at every scale, from nanometers (short range order, point defects, etc.), to micrometers (grain size, extended defects, etc.), to centimeters (texture, etc.). Similarly, relevant timescales range from atomic vibrations (picoseconds) to microstructural evolution times (hours to years). This extreme breadth of size and time scales makes the accurate simulations with fully-resolved atomic-scale tools (e.g., molecular dynamics) hopeless. Practical solutions must therefore rely on scale-bridging approaches that systematically upscale the lower scale physics into computationally tractable higher-scale constructs. The premise of this workshop is that extreme-scale computing can breathe new life into the field of multiscale modeling by addressing the problems identified above with brute force computing. This workshop will focus on new mathematical approaches to multiscale/multiphysics modeling, with a particular emphasis on the many theoretical and numerical challenges faced at the exascale. The goal is to bring together specialists in a range of massively parallel algorithms and researchers interested in improving the scalability of current techniques.

Part of the Long Program New Mathematics for the Exascale: Applications to Materials Science, Integration of direct simulations, online data analysis, and experimental data. Mathematical methods for data assimilation. Large-scale inverse problems. Computation-aided online experimental design at massive scales. Active exploration of chemical space using massive quantum calculations. Workflow infrastructure. Integration of numerically-intensive calculations with ML/data-science at scale.

Condensed Matter Physics and Materials,    Computational Physics and Numerical Simulation

Institute for Pure and Applied Mathematics (IPAM)

One of the key changes in the landscape of high-performance computing in materials science in the last decade is the explosion of high-throughput applications where massive amounts of relatively small quantum calculations fuel the rapid exploration of the chemical space of materials. Such high throughput workflows are prime candidates for the efficient exploitation of exascale resources. This workshop proposes to build on these early successes and to take the next logical step by exploring the challenges and opportunities associated with integrating massive-scale compute-intensive simulations into a wider range of complex scientific workflows. The underlying goal is to identify and explore opportunities to maximize the impact of large-scale computing by improving its integration with various aspects of the scientific enterprise. This workshop will aim at developing new mathematical and computational approaches that enable the inclusion of massive-scale computing into complex scientific workflows.

Part of the Long Program New Mathematics for the Exascale: Applications to Materials Science, Integration of direct simulations, online data analysis, and experimental data. Mathematical methods for data assimilation. Large-scale inverse problems. Computation-aided online experimental design at massive scales. Active exploration of chemical space using massive quantum calculations. Workflow infrastructure. Integration of numerically-intensive calculations with ML/data-science at scale.

The organizers of the XVI International Conference on Stochastic Programming (ICSP2022) are honored to host the tri-annual Conference at the University of California, Davis Graduate School of Management. The ICSP is the premier event of the Stochastic Programming Society (SPS) , a technical session of the Mathematical Optimization Society that brings together researchers who work on decisions under uncertainty, practitioners in the industrial and institutional sectors share recent theoretical and applied results. The conference aims to present the state-of-the-art in this field as well as neighboring scientific areas.