Bioinformatics, Genomics, & Data Science w/ Eleanor Howe

Описание: In this episode of Data Unchained, Molly Presley talks with Tracy Teal, Executive Director of the MathWorks Math Modeling Challenge, about the transformative role of mathematical modeling and data literacy in preparing students for real world problem solving. Tracy explains how the challenge, created by MathWorks and operated by SIAM, gives high school students a chance to analyze complex societal issues using math, coding and data. She describes how students work in small teams to develop assumptions, build models, gather public datasets, write code and generate a full report within a strict fourteen hour window.

Molly and Tracy discuss how the challenge has evolved over the past nineteen years. The problems have grown more interdisciplinary, incorporating climate science, economics, transportation, behavioral analysis, resource allocation and other domains that require students to apply both mathematical reasoning and computational tools. Tracy emphasizes that modeling is not about perfect answers but about learning to think critically, justify assumptions and communicate results clearly. She notes that students often surprise organizers with their creativity, rigor and ability to integrate real data sources into defensible solutions.

They explore how the challenge helps students build confidence and see the relevance of math in everyday life. Tracy shares examples of students applying linear programming, regression, simulation, optimization, probabilistic models and even agent based approaches to tackle questions that could easily belong in a college research program. Molly and Tracy also talk about how the event exposes students to career paths across engineering, data science, applied mathematics and public policy, and how teamwork teaches leadership, collaboration and time management under pressure.

The conversation turns to equity and representation in STEM. Tracy explains the efforts to broaden participation by supporting educators, simplifying registration, offering training resources and helping schools with limited access to advanced math courses. She emphasizes that modeling offers different entry points for students with varied strengths and encourages diverse approaches to reasoning and problem solving. Molly and Tracy also highlight the growing importance of data literacy as industries adopt AI, and how modeling skills help students navigate an increasingly data rich world.

Tracy describes what happens behind the scenes once submissions arrive. Reports undergo an intensive, multi stage blind review by judges drawn from academia and industry. These judges score clarity, modeling quality, assumptions, data use and analysis, ultimately selecting finalist teams to present their work in New York City. Molly and Tracy reflect on the excitement students feel when they see their work recognized at a national level and how the challenge often influences college choices and future career interests.

They close the episode discussing how modeling prepares the next generation to evaluate claims, test ideas, understand uncertainty and approach problems systematically. Tracy encourages students to believe that math is accessible, useful and empowering, and she invites educators and teams to explore the resources available for the next challenge cycle.

TIMESTAMPS
00:00 Intro
01:00 Tracy’s background and role at M3 Challenge
04:00 Overview of the Math Modeling Challenge
07:00 Fourteen hour model building structure
10:00 Interdisciplinary problem themes
13:00 Creativity and assumptions in modeling
16:00 Data literacy and real world relevance
19:00 Equity and broadening participation
22:00 How students use public datasets
25:00 Scoring, judging and blind review
28:00 Finalist presentations in New York
31:00 Career pathways from modeling
34:00 Encouraging confidence in math
37:00 Closing thoughts

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