paraDIGMS Spring 2021

paraDIGMS Spring 2021 Conference

Diversity in Graduate Mathematical Sciences

 

April 23-26, 2021

 

This online conference is the second conference in the American Mathematical Society’s paraDIGMS initiative to build a community of practice for graduate education in mathematics, with the goal of making the profession stronger and more equitable.

Math Institute workshop focuses on how math and statistics can address climate change | University of Chicago News

The
accelerating
effects
of
global
climate
change—including
destructive
wildfires,
intensifying
tropical
storms,
severe
drought and
coastal
flooding—pose
major
risks
to
civic
infrastructure,
the
natural
environment and
human
health.

To
address
these
challenges,
the

Institute
for
Mathematical
and
Statistical
Innovation
(IMSI)
at
the
University
of
Chicago
is
hosting
a
five-day
interdisciplinary
workshop
starting
March
1 that
brings
together
leaders
in
mathematics,
statistics and
atmospheric
sciences
to
begin
developing
tools
to
help
guide
responses
to
extreme
weather
events
at
a
local,
regional and
national
scale.

Confronting Climate Change

Confronting Climate Change

March 1-5, 2021

 

The workshop will bring together leaders in mathematics, statistics, and atmospheric sciences to confront grand climate challenges and their impacts. A major goal of the program will be to develop next-generation suites of science-driven mathematical and statistical tools and capabilities to address decision-relevant climate hazards and impacts.

Mathematical and Computational Materials Science

Mathematical and Computational Materials Science

February 15-19, 2021

 

Computational Materials Science is a branch of the engineering sciences that lies at the intersection of many disciplines. It describes how materials deform, are damaged, and age. This workshop identify questions where mathematics can play a significant role in the future.

Mathematical Advances in Mean Field Games

Mathematical Advances in Mean Field Games

December 13-17, 2021

 

Complex societal problems can be studied and modeled through the mathematical theory of Mean Field Games. Indeed MFGs are a mathematical modeling approach to stochastically evolving systems which involve a large number of indistinguishable rational agents that have the same optimization criteria. The theory of MFG is very lively and productive at the moment and several important results have been achieved that can be applied to engineering, economics, finance, social sciences, In this final workshop we present recent analytic, probabilistic and numerical advances in this theory.

Applications to Financial Engineering

Applications to Financial Engineering

December 6-8, 2021

 

Mean field theories, Mean Field Games, and Mean Field Control are theoretical concepts which can naturally be brought to bear in applications to financial engineering. The workshop will examine how they influenced the development of financial mathematics theoretical works and the implementation of financial engineering solutions to problems involving large ensembles of individuals or robots optimizing their behaviors in uncertain and complex environments.

Applications of Mean Field Games

Applications of Mean Field Games: from Models to Practice

November 16-19, 2021

 

The paradigm of Mean Field Games (MFG) has become a major connection between distributed decision-making and stochastic modeling. Starting out in the stochastic control literature, it is gaining rapid adoption across a range of industries. The objective of this workshop is to give a clear vision of how MFG tools are being used in practical settings, both in complement and in contrast to the usual methodologies. The workshop will gather researchers both from industry and universities and will focus on diverse application areas.

Mean-Field Models for interacting agents

Mean-Field Models for interacting agents

November 1-4, 2021

 

Interacting particle models are a powerful mathematical tool to model the behavior of large groups in economics as well as in the life and social sciences. Understanding the dynamics of these systems on different levels is of great importance, as it gives insights into the emergence of many complex phenomena. In this workshop we will focus on recent developments and emerging challenges in the derivation and analysis of these micro- and mean-field models. It will feature different perspectives and approaches to these challenges, by bringing together applied mathematicians working at the interfaces between statistics, social sciences and the life sciences.

Aggregate dynamics in models with heterogeneous agents

Aggregate dynamics in models with heterogeneous agents

October 27-29, 2021

 

This conference invites participants to present and discuss current research on models with the following features. The heterogeneous agents feature refers to agents solving dynamic problems subject to idiosyncratic random shocks, each agent with non-trivial interactions with the remaining agents. The “aggregate dynamics” feature refers to the focus on the understanding and characterization of the dynamics of the entire system, either itself subject to aggregate shock or as a deterministic system, using analytical or numerical techniques. Examples of such models are variants of Mean Field Games. Models will have applications in several fields in economics and intersections with other disciplines.