Data Science Updates is the University of Wisconsin-Madison's resource for news, training, events, and professional opportunities in data science, brought to you by the Data Science Institute, powered by American Family Insurance, and the Data Science Hub.
August 20, 2025
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The 2025 Machine Learning Marathon (MLM25) is a 12-week applied ML/AI hackathon running September 11 to December 11 at UW–Madison. Participants form teams of 2-5 and work on real-world challenges in areas like sustainable AI, protein modeling, brain decoding, biodiversity image clustering, retail forecasting, and more. The event includes workshops, advisor support, AWS credits, and cloud training. Open to anyone with ML, Python, and Git+GitHub fundamentals (enough to collaborate on a team).
Explore 2025 challenges: Review challenge-specific prerequisites and find something that fits your skills, interests, and learning goals:
Register individually by Sept 10. Tickets are limited and available on a first-come, first-serve basis — we recommend registering early to secure your spot. Team registration is due September 18th.
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In early July, Google announced the Google ML and Systems Junior Faculty Awards, a new program recognizing up-and-coming talent whose work intersects machine learning (ML) and systems. Of the over 50 recipients representing 27 U.S. universities, three come from UW–Madison’s Department of Computer Sciences (CS). Jelena Diakonikolas and Sharon Li, who are also Data Science Institute Affiliates, and Shivaram Venkataraman were selected to receive grants of $100,000 in unrestricted funding.
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August 25-28, 9:00 a.m. - 12:30 p.m.; Discovery Building, Orchard View Room. In this three-day, half-day workshop, participants will learn tools and practices for producing and sharing quality, sustainable, and FAIR (Findable, Accessible, Interoperable and Reusable) research software to support open and reproducible research. The target audience is graduate students, early career researchers, and research software engineers (RSEs) who are starting their research or software projects; have foundational knowledge of Python, version control, and using software tools from command-line shell; and want to develop software to support their research using established best practices. This workshop is also a great refresher for experienced researchers.
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August 25, 10:00 a.m. - 3:00 p.m.; 3218 Sewell Social Sciences Building. This workshop introduces the basics of the RStudio interface and the R language, with topics including creating and running scripts, saving your work, using functions, and installing packages. There will be opportunities to apply what we learn during class time.
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August 25, 10:00 a.m. - 3:00 p.m.; 4218 Sewell Social Sciences Building. In this class, you'll learn the basics of Stata. This class (or comparable experience) is a prerequisite for the rest of SSCC's Stata training. It will also prepare you to excel in classes that use Stata, like Sociology 361 or Economics 410. We suggest new graduate students consider taking this class before or during their first semester.
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August 26-29, 10:00 a.m. - 3:00 p.m.; 3218 Sewell Social Sciences Building. "Data wrangling" is the process of preparing data for analysis. This is a hands-on class with time devoted to practicing essential data wrangling skills. This course will first cover the tools needed to work with different data types. We will then apply these tools in the context of datasets to create, transform, and clean variables. We will also restructure datasets by taking subsets, combining multiple datasets, summarizing datasets, and changing how datasets are organized.
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August 26-28, 10:00 a.m. - 3:00 p.m.; 3218 Sewell Social Sciences Building. Data wrangling is a critical skill for research. In this class, you'll learn how to wrangle data using Stata. We'll cover some key concepts and workflows of data science and the structure and logic of Stata. We'll emphasize real-world issues like handling missing data, checking for errors, and best practices for research computing and reproducibility. Our goal is to give you a strong foundation you can build on to become an expert data wrangler.
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September 8, 5:30 p.m. - 7:00 p.m.; 2257 College Library & Zoom. Curious about coding but don’t know where to start? This workshop unpacks programming and coding from the ground up. It explains the terms and structures used in most modern programming languages and introduces some basic computer science concepts in an accessible, easy to digest format with no technical background knowledge required.
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September 8, 5:30 p.m. - 7:00 p.m.; 2538 Morgridge Hall & Zoom AND September 9, 5:30 p.m. - 7:00 p.m.; 2257 College Library & Zoom. Python is a powerful, popular programming language that gets used for just about everything: basic coding, graphics processing, machine learning, AI, web scraping, data analysis, and much more. This workshop introduces basic Python concepts that will help you get coding in no time – no previous programming experience required!
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September 10, 5:30 p.m. - 7:00 p.m.; 2257 College Library & Zoom. In this workshop, students explore the favorite tool of many creative professionals, Adobe Illustrator. Used by designers and artists around the world, this powerful vector graphics program makes it easy to create logos, posters, product labels, icons, website mockups, and more. Students will learn the basics of Illustrator, work with shapes, text, and color, and create a project from scratch.
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September 11, 5:30 p.m. - 7:00 p.m.; 2257 College Library & Zoom. Need to use git for class, but don’t know where to start? This workshop covers the basics of using git for version control. It explores how to use it with the popular cloud-based platform GitHub using the GitHub desktop app – no previous knowledge of git, GitHub, or command lines required! This workshop will cover creating file repositories, commits, pushing and pulling repositories from GitHub, merging, branches, and conflicts.
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September 11, 5:30 p.m. - 7:00 p.m.; 2538 Morgridge Hall & Zoom. The free, open-source programming language R has become one of the most widely used tools for data analysis and statistical computing today. This workshop introduces learners to the basics of the language, the RStudio development environment, and some of the most common functions, packages, and tools in the R ecosystem.
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September 15, 5:30 p.m. - 7:00 p.m.; 2538 Morgridge Hall & Zoom. This workshop was curated to facilitate an understanding of the broad topic of Artificial Intelligence for both beginners and those with prior programming experience. In our engaging sessions, we’ll demystify complex concepts like gradient descent, learning rates, privacy, bias, as well as delve into the realms of supervised and unsupervised learning, empowering you with foundational AI knowledge that transcends programming proficiency.
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September 16, 5:30 p.m. - 7:00 p.m.; 2257 College Library & Zoom. As one of the flagship programs of the modern publishing industry, Adobe InDesign is used for all kinds of print and digital publications. From student org brochures and departmental newsletters to professional magazines and newspapers, InDesign is the tool of choice for laying out and publishing documents. In this workshop, students will learn how to set up projects in the InDesign workspace, incorporate external text and images, add styling to type and graphics, and export projects for publishing.
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September 16, 5:30 p.m. - 7:00 p.m.; 2538 Morgridge Hall & Zoom. This workshop is an introduction to working with data in Excel. Students will learn spreadsheet terminology, the basics of the Excel interface, how to create and edit spreadsheets, and how to generate charts and graphs from data.
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Have questions about anything data science-related? Come see the Data Science Hub facilitators at Coding Meetup on Tuesdays and Thursdays from 2:30-4:30 p.m. CT. To join Coding Meetup, join data-science-hubgroup.slack.com.
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Summer SILO Finale: Poisoning Language Models
TODAY August 20, 4:00 p.m. - 5:00 p.m.; Memorial Union (0008)- Multicultural Greek Council Room (4th Floor). In this talk, we introduce Charmer, a gradient-free character-level adversarial attack framework that achieves high attack success rates with few character modifications per input. Charmer performs well on discriminative and generative language models, demonstrating its versatility even in systems fortified with adversarial training. The interplay between character-level attacks and automated typographical correctors offers an interesting trade-off.
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September 4, 1:30 p.m. - 2:30 p.m.; UW Biotechnology Center Auditorium, Genetics-Biotechnology Center Building & Zoom. Speaker: Dr. Brian Davis, Texas A&M, is an evolutionary biologist who is interested in how genomes and organisms evolve when under natural and artificial selection.
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- Data Entry Operator, Wisconsin Reading Center
- Institutional Policy Analyst, UW-Madison Office of Data, Academic Planning & Institutional Research
- Research Analyst, UW-Madison School of Medicine & Public Health, Medical Education Office
- Research Assistant Professor in Analysis of Biomedical Data, University of Chicago, Department of Family Medicine, Biological Sciences Division
- Research Quality Assurance and Validation Specialist, UW-Madison School of Medicine & Public Health
- Scientist I, UW-Madison Institute on Aging
- Tracing Supervisor, UW-Madison Survey Center
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DATA VISUALIZATION OF THE WEEK
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10,000 years ago, 57% of the world’s habitable land was covered by forest. In the millennia since then, a growing demand for agricultural land means we’ve lost one-third of global forests — an area twice the size of the United States. Half of this loss occurred in the last century alone.
It's possible to end our long history of deforestation. Increased crop yields, improved livestock productivity, and technological innovations that allow us to shift away from land-intensive food products give us the opportunity to bring deforestation to an end and restore some of the forest we have lost.
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Reposted from Our World in Data: Research and data to make progress against the world’s largest problems.
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Data Science Updates is a collaborative effort of the Data Science Institute and Data Science Hub. This newsletter was originally created by the Data Science Hub and published as Hub Updates.
Use our submission form to send us your news, events, opportunities and data visualizations for future issues.
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