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You are here: Home / Featured Stories / SDSS2023: Diverse Panels, Engaging Discussions, Memorable Experiences

SDSS2023: Diverse Panels, Engaging Discussions, Memorable Experiences

August 1, 2023 Leave a Comment

Emily Dodwell, SDSS 2023 Program Chair
From left: Panelists Jeri Mulrow, Ming Li, and Felicia Simpson open the first day with a discussion about the motivations, challenges, and accomplishments that go hand-in-hand with new career opportunities in “Exploring New Paths: Reinvigorating Your Career.”

The St. Louis Union Station Hotel served as the backdrop for the 2023 Symposium on Data Science and Statistics, which welcomed attendees from across academia, industry, and government. This year’s theme—“Inquire, Investigate, Implement, Innovate”—served as a representation of the iterative process required to pursue new opportunities and power unexpected breakthroughs. It was intended to be relevant to the various stages of a data scientist’s career and the twists and turns of a data science project, regardless of the specific area or application.

Ron and Jeri stand in front of a punch bowl laughing.
ASA Executive Director Ron Wasserstein makes Jeri Mulrow laugh during a break at SDSS 2023.

The program was anchored by three plenary panels. Felicia Simpson, Jeri Mulrow, and Ming Li opened the first day with a discussion about the motivations, challenges, and accomplishments that go hand-in-hand with new career opportunities in “Exploring New Paths: Reinvigorating Your Career.” The next day’s panel, titled “Communicating Statistics: Tools, Tips, and Tricks,” featured Christine Zhang, Roger Peng, and Sara Stoudt. They led a lively conversation about their favorite data visualizations and elements that make them effective. In the third panel, “Open-Source Software: From Creation to Evaluation,” Carol Willing, Daniell Toth, and Tracy Teal provided attendees with several on-ramps for engaging in various open source communities.

Attendees’ engagement with the panelists was evidenced by conversations that spilled into hallways and continued well after the plenary sessions ended.

Additionally, many of the panelists attended poster sessions and coffee breaks and arrived early to serve as mentors during the speed mentoring breakfast.

St. Louis Union Station provided ample opportunity for new friends and longtime colleagues to connect with its variety of restaurants and attractions within steps of the hotel. After enjoying toasted ravioli—one of the city’s signature dishes—at the opening mixer, several attendees took in the Fire and Light show. Staged on a lake outside the hotel, this hourly display times pumping music to bursts of fire shot out of lotus-shaped pods. Other attendees visited the St. Louis Aquarium during a lunch break or walked the mile and a half down Market Street to take in the Gateway Arch.

From left: Panelists Sara Stoudt, Roger Peng, and Christine Zhang discuss their favorite data visualizations in “Communicating Statistics: Tools, Tips, and Tricks.”

This year’s program committee incorporated feedback from prior years into this year’s program logistics and extracurricular offerings. Following requests from attendees last year to note the difficulty level of talks in the program, the committee included the speakers’ intended target audience as a point of reference (i.e., expert, mid-level, and beginner). This enabled attendees to craft a schedule that best reflected their levels of experience with material across the six tracks. Also, to support additional meeting and greeting, the committee planned a well-attended mini golf outing, during which participants in small groups tried their hands at an 18-hole course.

Amanda Koepke, a mathematical statistician at the National Institute of Standards and Technology, will chair the program for SDSS 2024.

View more photos of the event.

Filed Under: Featured Stories, Meetings, Symposium on Data Science and Statistics Tagged With: Amanda Koepke, Chistine Zhang, Jeri Mulrow, Roger Peng, Ron Wasserstein, Sara Stoudt, SDSS 2023, St. Louis, St. Louis Union Station, Symposium on Data Science and Statistics, Tracy Teal

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