March/April 2021 Newsletter

IMSI Launches Graduate Student Internship Program

IMSI will launch a new paid internship program for Ph.D. students in mathematics and statistics this summer. The program will be hosted by the University of Illinois at Urbana-Champaign, and will build on prior success with the PI4 Internship Program. Internships will be hosted primarily by companies and scientific labs in Champaign-Urbana, Illinois.

There are seven internships available for the summer of 2021. The program will begin with a two-week skills workshop (May 22-June 6, 2021) on computation and data science. Prior coding experience is not required. Students will then be placed in internships for eight weeks during the summer.

It is likely that the ongoing pandemic will result in some or all of the activity related to this program taking place in an online format. Decisions about this will be made closer to the beginning of the program.

Coming Activities

Spring 2021

April 12-16: The Multifaceted Complexity of Machine Learning

April 26-30: Topological Data Analysis

May 10-14: Verification, Validation, and Uncertainty Quantification Across Disciplines

May 17-21: Decision Making in Health and Medical Care: Modeling and Optimization

May 24-28: Quantum Information for Mathematics, Economics, and Statistics

Summer 2021

June 1-25: Introduction to Mean Field Games and Applications

This program provides mathematical background for the long program in Fall 2021 on Distributed Solutions to Complex Societal Problems. Problems to be addressed in the long program include modeling of phenomena such as the macroeconomy, conflict, financial regulation, crowd movement, big data, and advertising, as well as engineering problems involving decentralized intelligence, machine learning, and telecommunications. A mathematical framework well-suited to the study of such phenomena is Mean Field Games. The intended audience consists of advanced graduate students, postdocs, and researchers interested in the general topic who have some knowledge of probability, stochastic analysis, and partial differential equations.

This program will take place online. Some financial support is available for participants who need it.

June 28-July 23: Introduction to Decision Making and Uncertainty

How do we make decisions in the face of risk? The need to make decisions in the presence of uncertainty cuts across a wide range of issues in science and human behavior. The underlying problems require both sophisticated modeling and advanced mathematical and statistical approaches and techniques.

This program will serve as an introduction to the long program on Decision Making and Uncertainty scheduled for Spring 2022. It aims to introduce participants to a variety of modeling questions and methods of current interest in this area. The intended audience is researchers interested in mathematical modeling and methods applicable to decision making under uncertainty in economics, finance, business, and other areas. Advanced Ph.D. students, postdocs, and junior faculty are especially encouraged to apply. Basic knowledge in probability, stochastics, and statistics is required.

This program will take place online. Some financial support is available for participants who need it.

August 30-September 3: Eliciting Structure in Genomics Data: Bridging the Gap between Theory, Algorithms, Implementations, and Applications

2021-2022

Fall 2021 Long Program: Distributed Solutions to Complex Societal Problems

The need to understand and model large populations of rational agents interacting through intricate networks of connections is ubiquitous in modern science. Problems along these lines arise in settings such as the economy, global conflicts, and the spread of diseases, and they raise consequential policy issues. Population control, crowd analysis, smart cities, and self-driving vehicles present problems of a similar nature that are often tackled with tools such as machine learning and artificial intelligence. However, in spite of spectacular successes, the lack of a deep understanding of how robots and human beings learn to navigate their environments and make forward looking decisions remains a major impediment to systematic progress, and the debate on the relative merits of centralized versus decentralized intelligence remains very much alive. This program will address problems along these lines using the mathematical framework of Mean Field Games.

Spring 2022 Long Program: Decision Making and Uncertainty

Economics, finance, and business activities like marketing, operations management, and R&D all substantially rely on the use of formal, mathematical approaches to model human behavior, agents’ interaction, trading exchanges, mitigation of risks, and more. However, these areas are all rich enough that many important challenges are as yet unmet and new ones are constantly arising. For example, recent advances in data science, new platforms and means of human interaction, the growing speed of trading exchanges and flow of information, and various technological and other breakthroughs are all fertile ground motivating the use of new mathematical and statistical models and methods.

IMSI Seeks Program and Workshop Proposals

IMSI is seeking proposals for workshops to be held in the winter of 2022. Workshops are intended to be interdisciplinary and focused on a societally-relevant topic for which mathematicians and statisticians can partner with other sciences to make important contributions. Workshop organizers are expected to attract a diverse group of participants, where diversity is measured across a number of dimensions, including gender, race, ethnicity, career stage, employment sector, and research area. The deadline for this round of proposals is May 1, 2021.

IMSI is seeking proposals for long programs for the academic year 2023-24 and workshops in 2023 and beyond. The deadline for this round of proposals is September 1, 2021.

General expectations for proposals are discussed on IMSI's Proposing Activity web page. If you have an idea for a program or workshop, please contact Kevin Corlette ([email protected]) to initiate a dialogue.

IMSI Adds Staff, Accelerating Its Startup Phase

IMSI has recently hired it's first two staff members.

Our first hire is Philip (Bo) Hammer, who became our Executive Director on January 1. Bo comes to IMSI from the American Institute of Physics, where he was the founding and interim Executive Director of the AIP Foundation. He also led AIP’s major antiracism initiative that addressed under representation of African Americans in physics and astronomy. Bo received his BS in Physics from Humboldt State University, in the redwoods of northern California, and his PhD in Physics from the University of Oregon. After two years doing postdoctoral research in experimental nonlinear dynamics and chaos at the Naval Surface Warfare Center, he spent a year as Congressional Science Policy Fellow working on the staff of the Subcommittee on Science in the US House of Representatives. This experience immersed him in the world of science policy and launched his subsequent career as a nonprofit executive. Bo loves to swim and bike where and whenever he can. These past twelve months of pandemic have not only led to personal-best cycling miles, but a newfound passion for baking.

IMSI’s second hire is Denise Slavinski, who became our Assistant Director on February 27. Originally from Atlanta, GA, Denise lived in Montreal, QC and Houston, TX before settling in Chicago. She holds a MA in English from McGill University, and a dual-BA in English and Global Studies with a minor in Spanish from the University of West Georgia. Before joining the IMSI staff, she was the Operations Manager of the English Language Institute at the University of Chicago. Prior to coming to the University of Chicago, Denise worked in real estate in the Atlanta area. Her interests include learning languages, cooking and baking, and reading science fiction and fantasy.

We plan to hire several more staff members over the next few months, with the goal of reaching a full complement by the fall.

IMSI Deploys Math and Statistics to Tackle Major Societal Challenges

As the newest of the NSF Mathematical Sciences Institutes, IMSI is distinctive in its mission to bring applied mathematicians and statisticians together to conduct research on major societal challenges in collaboration with scientists from other disciplines. IMSI has six scientific themes: Climate Science, Data and Information, Health Care and Medicine, Materials Science, Quantum Computing ad Information, and Uncertainty Quantification. These six themes naturally connect across the disciplines and address a range of issues that are central to the challenges and opportunities currently confronting our global society.

IMSI has wasted no time in getting to work on the most urgent of these. For example, IMSI’s first targeted scientific workshop was on Dealing with COVID-19 in Theory and Practice. This two-day workshop, October 29-30, 2020, brought together an international, multidisciplinary group of scholars to address three topics: Public Health Challenges, The Role of Data Science, and Measuring and Managing Economic Impact. Speakers addressed these topics from a variety of perspectives, including those of governments and the private sector, with the goal understanding the interconnected complexities created by the pandemic and gaining insights into how IMSI’s scientific community can contribute to near-term solutions and better preparedness for the next pandemic

Similarly, IMSI is currently holding a five-day workshop on Confronting Climate Change, March 1-5, 2021. This workshop is designed to develop next-generation mathematical and statistical tools that scientists and policy makers can use in addressing climate hazards and impacts. Similar to the structure of previous workshops, the program has been organized to introduce participants to current research across a range of key topics spanning physics, oceanography, climate and weather, risk assessment and mitigation, and science-based policy making – all with a lens on key contributions from applied mathematicians and statisticians.

Making progress in dealing with pandemics and climate risk requires acquiring and analyzing unprecedented quantities of data from a variety of sources using techniques that are as novel as the problems they are addressing. Advancing the societal good and protecting life and property requires software and hardware tools that are reliable, accurate, and that produce results that are consistent with social values, laws, and regulations. Typical software concerns are bias in artificial intelligence algorithms, the use of neural networks and machine learning to supplement and augment human decision-making, and structuring large quantities of data so that meaningful information can be extracted. All of this assumes that the computers used to acquire, manage, and process data are fast, reliable, and energy efficient. These issues quickly converge on questions of materials science and next generation computing, such as quantum computing.

IMSI’s first workshop to address Materials Science was held February 15-19, 2021. As with previous workshops, this one was virtual and focused on understanding the basic tools mathematicians, physicists, and materials scientists use to understand economically critical materials at the atomic level. For example, how can artificial intelligence be used to simulate the properties of novel superconductors, which will be necessary for future quantum computers? The workshop was designed to bring a diverse group of researchers together to explore such questions and form collaborative teams whose work may lead to economically and societally relevant new devices for handling tomorrow’s major computing and other challenges that require new materials.

Copyright © 2021. All rights reserved.
IMSI acknowledges support from the National Science Foundation
(Grant No. DMS-1929348)

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