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The next event is coming soon on Friday, February 24th, 2023, at 1pm PT/2pm MT/3pm CT/4pm ET. Industry panelists from Wells Fargo will be Paul Romanelli, managing director and head of the Corporate Risk Model Development Center; and Tracey Tullie, quantitative analytics director. All participating students will get the opportunity win one of five US$25 amazon gift cards.

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Register for the Zoom event here: https://umsystem.zoom.us/meeting/register/tJwvc-qppz4jHtQIc4H81wyNe9kYLmIzviUt

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See our website for more information: https://bigmathnetwork.org/2023/02/20/big-math-network-industry-connection-series-wells-fargo/

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*The BIG Math Network is grateful for sponsorship by the American Mathematical Society (AMS), the American Statistical Association (ASA), the Institute for Operations Research and the Management Sciences (INFORMS), the Mathematical Association of America (MAA), and the Society for Industrial and Applied Mathematics (SIAM).*

You can register through this site

]]>- What is the role of a mathematician in business and industry?
- What is it like to work with technical experts on a problem that requires significant mathematics but also must satisfy real-world constraints?
- What kind of mathematical and statistical tools are used to solve problems in business and industry?

The REU program at WPI provides a unique experience that answers these questions, an experience that complements standard academic training.

For more information, see the CIMS REU webpage, and applications can be submitted through mathprograms.org:

]]>The GSMMC is a workshop designed to teach graduate students a broad range of problem-solving skills, including mathematical modeling and analysis, scientific computation, and critical assessment of solutions. Guided by an invited faculty mentor, students work in teams on highly interdisciplinary problems inspired by real industrial applications. As a result, the GSMMC provides a valuable educational and career-enhancing experience outside of the traditional academic setting.

The following problems were analyzed at the 2022 GSMMC:

- Modeling the tradeoffs in publishing urban travel data sets
- Cloudy with a chance of snow: The life of a snowflake in a cloud microphysics model
- Asymmetric division and modeling of interacting cell populations in the colonic crypt

Applications must be completed by **April 21, 2023** for full consideration, and successful applicants will be notified by early to mid-May.

**Full financial support is available for all participants**. The selection will be based on academic background and interests as indicated in the application form and on a letter of recommendation from a faculty sponsor. Women and students from underrepresented groups are especially encouraged to apply.

https://wpi.qualtrics.com/jfe/form/SV_bjCyeqQnVmK8TUq

More information on MPI 2022 can be found at the workshop website. Any further questions can be sent to Prof. Burt Tilley (tilley@wpi.edu)

]]>MPI is a problem solving workshop that attracts leading applied mathematicians and scientists from universities, industry, and national laboratories. During the workshop, engineers and scientists from industry interact with the academic participants on problems of interest to their companies. In the past, these problems have included, but are not limited to

- engineering and product design
- process design and control
- environmental remediation
- scheduling and optimization
- financial modeling

More information can be found at the MPI 2022 website.

WPI has hosted the workshop 4 times previously: in 2003, 2005, 2008, and 2013.

]]>**Abstract:**We propose a mean field game model to study the question of how centralization of reward and computational power occur in the Bitcoin-like cryptocurrencies. Miners compete against each other for mining rewards by increasing their computational power. This leads to a novel mean field game of jump intensity control, which we solve explicitly for miners maximizing exponential utility, and handle numerically in the case of miners with power utilities. We show that the heterogeneity of their initial wealth distribution leads to greater imbalance of the reward distribution, and increased wealth heterogeneity over time, or a “rich get richer” effect. This concentration phenomenon is aggravated by a higher bitcoin price, and reduced by competition. Additionally, an advanced miner with cost advantages such as access to cheaper electricity, contributes a significant amount of computational power in equilibrium. Hence, cost efficiency can also result in the type of centralization seen among miners of cryptocurrencies.

**Abstract:**The dynamics of many models in Biology and Ecology such as: epidemic models, tumor-immune models, chemostat models, prey-predator models, competitive models, and among others can be mathematically described. The earliest and simplest mathematical models are given by ordinary differential equations (ODE). Long-standing and important questions in mathematical biology are that: How is the long-time behavior of the system? Does one group of populations come extinct or persistent? Under which condition, the disease will be controlled in the epidemic systems?. In longtime, which species dominates the others? and among others. This talk focuses on modeling these above biological and ecological systems and answering such problems when the random factors (leading to stochastic system), past-dependence (leading to delay system), spatial inhomogeneity (leading to reaction-diffusion models) are taken into consideration, which are described under stochastic differential equations (SDEs), stochastic functional differential equations (SFDEs) and stochastic partial differential equations (SPDEs) framework. .

**Abstract:**We consider heterogeneously interacting diffusive particle systems and their large population limit. The interaction is of mean field type with random weights characterized by an underlying graphon. The limit is given by a graphon particle system consisting of independent but heterogeneous nonlinear diffusions whose probability distributions are fully coupled. A law of large numbers result is established as the system size increases and the underlying graphons converge. Under suitable additional assumptions, we show the exponential ergodicity for the system, establish the uniform in time law of large numbers, and introduce the uniform in time Euler approximation. The precise rate of convergence of the Euler approximation is provided. Based on joint works with Erhan Bayraktar and Suman Chakraborty.