Konferenzen zum Thema Statistik, Spieltheorie in den Vereinigten Staaten (USA)

American Statistical Association

SDSS 2022 will offer many occasions to learn about new data tools and methodologies, see data science in action, and network with experts.

Beyond Big Data: Influencing Science, Technology, and Society

Institute of Mathematical Statistics

ICERM

A challenge for mathematical modeling, from toy dynamical system models to full weather and climate models, is applying data assimilation and dynamical systems techniques to models that exhibit chaos and stochastic variability in the presence of coupled slow and fast modes of variability. Recent collaborations between universities and government agencies in India and the United States have resulted in detailed observations of oceanic and atmospheric processes in the Bay of Bengal, the Arabian Sea, and the Indian Ocean, collectively observing many coupled modes of variability. One key target identified by these groups was the improvement of forecasts of variability of the summer monsoon, which significantly affects agriculture and water management practices throughout South Asia. The Monsoon Intraseasonal Oscillation is a northward propagating mode of precipitation variability and is one of the most conspicuous examples of coupled atmosphere-ocean processes during the summer monsoon. Simulating coupled atmosphere-ocean processes present mathematical challenges spanning numerical methods, data assimilation, stochastic modeling, dynamical systems and chaos, and uncertainty quantification. Predicting monsoon variability is one of the hardest, most important forecasting problems on earth due to its impact on billions of people, a key aspect of the desire to push weather forecasts into the management-actionable “medium-range” horizon of weeks to seasons. Addressing this challenge requires an interdisciplinary effort to combine observations, computation, and theory. A better understanding of these processes and how they can be represented in a variety of coupled ocean-atmosphere simulations and models (including statistical and dynamical approaches) and forecast systems (including data assimilation techniques and uncertainty quantification) is the primary topic of this workshop. While the set of observations to be discussed will emphasize this region, the mathematical and computational aspects of the program will be significantly broader, covering: coupled ocean-atmosphere modeling for weather models, climate models and idealized models; theory of the atmospheric and oceanic boundary layers, and waves on the interface; data assimilation in coupled modeling systems; and numerical methods for coupled systems.

Program Staff;     Tel.: [1-401-863-5030];     Email: info@icerm.brown.edu

Cornell University

Stochastic networks is a multifaceted area of research concerned with the modeling, stability, control, performance, approximation, and design of stochastic networks. It gives rise to challenging and subtle mathematical problems, whose solution often requires a combination of ideas and techniques from several branches of mathematics, including probability theory, stochastic processes, analysis, optimization, algorithms, combinatorics, and graph theory. Research in this area is strongly motivated by applications in diverse domains, ranging from the traditional areas of telecommunications and manufacturing to service operations, biological and social networks, revenue management, and health care. The series of conferences on Stochastic Networks, initiated in 1987 and now held biennially, is a major forum for researchers to learn of the latest developments and new research directions in stochastic networks.

ICERM- Brown University

This symposium is designed to bring together statistical and data science researchers either working directly in the area of HIV or whose work has direct relevance to problems and data structures encountered in HIV research. We are particularly interested in engaging data science researchers in fields such as computer science, engineering, and applied mathematics, whose work in related areas might lead to innovative new approaches.

Tel.: [4018635019];     Email: Kellie_shaughnessy@icerm.brown.edu

statistical, data science, HIV

Institute for Pure and Applied Mathematics (IPAM) at UCLA

As algorithmic decisions and likelihood predictions reach ever more deeply, and with increasing consequence, into our lives, there is an increasing mandate that they be “fair”. Who counts? Machine learning algorithms learn from training data; when these are biased so are the algorithms they produce. The workshop will examine sources of sex and gender bias in data, with emphases on impoverished women; women of color; trans and non-binary persons; and older women. This program is preceded by a Graduate Summer School on Algorithmic Fairness organized by Cynthia Dwork, and Guy Rothblum (Weizmann Institute of Science).

JSM Is … One of the Largest Statistical Events in the World — More than 6,500 attendees from 52 countries; 600+ sessions, including invited, topic-contributed, contributed, and poster; More than 1,000 student attendees; 75+ employers hiring for more than 200 positions; 80+ exhibitors; and 13 participating societies. It is also one of the broadest, with topics ranging from statistical applications to methodology and theory to the expanding boundaries of statistics, such as analytics and data science. JSM also offers a unique opportunity for statisticians in academia, industry, and government to exchange ideas and explore opportunities for collaboration. Beginning statisticians (including current students) can learn from and interact with senior members of the profession.

Texas A&M University, College Station, TX

The goal of this in-person conference is to bring together researchers studying nonsmooth spaces from different perspectives, facilitating the exchange of ideas, problems, and mathematical techniques. Perspectives coming from probability, analysis on metric spaces, and Banach space theory are of particular emphasis. Interactions among these different fields have already proven exceptionally fruitful. For example, a famous fractal space constructed by Laakso to answer a purely metric measure theoretic question inspired a similar construction (pictured above) eventually used to characterize superreflexivity in Banach spaces. Later, uniform q-convexity, a quantitative refinement of superreflexivity, was metrically characterizing using Markov convexity – a measurement of the diffusivity of Markov processes in a metric space. Together with many more examples, these show how shared geometric objects play important roles in each subject while being viewed through different lenses. More interactions of this type will be necessary to solve important open problems, such as analyst’s traveling salesman-type problems and metric characterizations of other Banach properties.

Geometrie und Topologie,    Analysis

Held every 3 years, ICOSDA provides a platform for researchers and practitioners to share and discuss recent advances in distribution theory and its applications. The conference encourages opportunities for research collaborations.

American Statistical Association

American Statistical Association

American Statistical Association (ASA)