Stories From 2025 I/O Magazine
Could the waters colored green by neurotoxin-releasing algal blooms be causing outsized rates of ALS? Visit this close-knit community as researchers work to reclaim their gorgeous home from fear and uncertainty.
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Just as important as inputs and outputs is the slash between them; the planning, the infrastructure, the programs, the relationships. I/O Magazine provides new ideas and fresh inspiration to make your slashes better.
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Hear from leaders who have successfully navigated troubled waters and major changes on a national scale.
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Join Retired Gen. Charles Q. Brown Jr. for a conversation on what it takes to include empathy and character in education.
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Listen to two recent PhD alumni who are leading successful startups for their words of wisdom to those looking to follow in their footsteps.
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Find out how two former high school teachers are making sure their programs designed to spread STEM inspiration to K-12 students aren't forgetting their teachers.
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technology with a human touch |
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Discover how virtual reality technology is leaving behind its pixelated roots to redefine a wide range of clinical practices.
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Come along for a discussion on whether adding human-like emotions to AI assistants and robots is helpful or hurtful.
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Learn how engineers are balancing the very real costs and benefits of capturing people's long-term health data through wearable technology.
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Take a peak at some of the coolest, most powerful research tools empowering scientists to uncover insights into everything from electronics to medicine.
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Professor Jessilyn Dunn is the leader of the Big Ideas Lab, where she studies how wearable technology allows us to better understand our bodies. Find out how it all works.
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Seven Duke Engineering faculty members welcomed new daughters over the course of a year. Discover how this unlikely cohort found support not only within this group, but through the wider Duke community.
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“Insurance companies need new ideas and strategies that account for the challenges of climate change and that can be modeled or tested at some capacity before being implemented at larger scales.”
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