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SUMMARY:Lectures in Data Visualization: Arvind Satyanarayan
DESCRIPTION:Intelligence Augmentation through the Lens of Interactive Data Visualization \nThe rise of large language models has brought new urgency to the future of human + machine partnerships. In this talk\, I will use three research threads on interactive data visualization to better understand the balance between automation and augmentation. First\, I will describe how new specifications of visual and non-visual data representations allow us to reason about visual perception and cognition. Second\, I will explore how visualization can be used to bridge human mental models and machine-learned representations. And\, finally\, I will discuss how data visualization already exhibits an epistemological crisis of truth—one that generative models threaten to further widen. \nRegister to Attend \n\nAbout the Speaker \n\nArvind is an Assistant Professor of Computer Science at MIT\, where he leads the Visualization Group at MIT CSAIL. His research uses interactive data visualization as a petri dish to study intelligence augmentation\, or how do computational representations and software systems help amplify our cognition and creativity while respecting our agency?   His work has been recognized with an NSF CAREER award\, best paper awards at academic venues (e.g.\, ACM CHI and IEEE VIS)\, and honorable mentions amongst practitioners (e.g.\, Kantar’s Information is Beautiful Awards). Systems he has helped develop are widely used in industry\, on Wikipedia\, and in the Jupyter/Python data science communities.  Arvind received his PhD from the Computer Science department at Stanford University\, working with Jeffrey Heer and the UW Interactive Data Lab. \nAbout the Series\nThe Brown Institute at Columbia Journalism School\, in partnership with the Data Science Institute and the Department of Computer Science\, is excited to present a lecture series that delves into the art and science of data visualization. This dynamic interdisciplinary series will explore the ways in which technology is transforming how we encounter\, comprehend\, and create data-driven narratives. The series will take place every other Thursday over the lunch hour from March to May\, and will feature esteemed experts in these fields. Over the course of a few months\, we will explore the profound impact that the tools and techniques utilized in data visualization have on the stories we can tell. \nThe series will include five lectures\, led by renowned experts including Cindy Xiong\, Dom Moritz\, Arvind Satyanarayan\, Jen Christiansen\, and Gurman Bhatia. The topics to be covered in the series are diverse and thought-provoking\, encompassing the role of ML in data visualization\, the design process for best representing the stories behind the data\, the future of interactive visualization\, and the very role tools play in our approaches to graphics. Whether you’re a data scientist\, a journalist\, a technologist\, a storyteller\, or a combination thereof\, this series will explore a practice that spans all disciplines. Join us as we hear from these experts and engage in interactive discussions exploring the latest advancements in data visualization and technology. \nJoin us for a lecture followed by a small reception\, all held in the Brown Institute for Media Innovation on the entry floor of Pulitzer Hall (Journalism School). Registration required. \n 
URL:https://brown.columbia.edu/event/lectures-in-dataviz-asatyanarayan/
LOCATION:Brown Institute at Columbia\, 2950 Broadway\, New York\, NY\, 10027\, United States
CATEGORIES:Lectures in Data Visualization
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ORGANIZER;CN="Brown Institute @ Columbia":MAILTO:browninstitute@columbia.edu
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DTSTART;TZID=America/New_York:20230420T120000
DTEND;TZID=America/New_York:20230420T133000
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SUMMARY:Lectures in Data Visualization: Jen Christiansen\, Scientific American
DESCRIPTION:Special Considerations for Science Graphics\nJen Christiansen\, Scientific American\n \nScience graphics are beholden to the same design principles as other types of graphics. But the information they hold is often the product of a process that a lot of people in your audience may not be familiar with. It’s important to honor the fact that the data you’re presenting is both the product of a rigorous study that builds upon past studies\, and that interpretations may eventually shift a bit as future research sheds more light on the topic. This session provides you with some strategies for addressing those challenges. In particular\, three overarching themes that are particularly pertinent to science graphics: honoring complexity\, avoiding misinformation pitfalls\, and visualizing uncertainty. \nRegister to Attend \nAbout the Lecture Series\nThe Brown Institute at Columbia Journalism School\, in partnership with the Data Science Institute and the Department of Computer Science\, is excited to present a lecture series that delves into the art and science of data visualization. This dynamic interdisciplinary series will explore the ways in which technology is transforming how we encounter\, comprehend\, and create data-driven narratives. The series will take place every other Thursday over the lunch hour from March to May\, and will feature esteemed experts in these fields. Over the course of a few months\, we will explore the profound impact that the tools and techniques utilized in data visualization have on the stories we can tell. \nThe series will include five lectures\, led by renowned experts including Cindy Xiong\, Dom Moritz\, Arvind Satyanarayan\, Jen Christiansen\, and Gurman Bhatia. The topics to be covered in the series are diverse and thought-provoking\, encompassing the role of ML in data visualization\, the design process for best representing the stories behind the data\, the future of interactive visualization\, and the very role tools play in our approaches to graphics. Whether you’re a data scientist\, a journalist\, a technologist\, a storyteller\, or a combination thereof\, this series will explore a practice that spans all disciplines. Join us as we hear from these experts and engage in interactive discussions exploring the latest advancements in data visualization and technology. \nJoin us for a lecture followed by a small reception\, all held in the Brown Institute for Media Innovation on the entry floor of Pulitzer Hall (Journalism School). Registration required. \nAbout the Speaker \n \nPhotograph by Liz Tormes \nJen Christiansen is a science communicator specializing in visual media\, the individual produces explanatory diagrams and data visualizations. She is the author of Building Science Graphics\, a publication by A K Peters/CRC Press\, and holds the position of senior graphics editor at Scientific American. Jen strives to create engaging and informative images catering to specialist and non-specialist readers. She possesses the ability to comprehend\, interpret\, and communicate scientific concepts visually\, whether it involves illustrating complex processes or assisting readers in navigating a story. Although she is capable of producing final renderings\, they also collaborate with freelance illustrators\, data designers\, and researchers on a project-by-project basis\, as demonstrated by their work on this site. \nSince 2007\, Christiansen has held the position of graphics editor at Scientific American. However\, their association with the magazine dates back to 1996 when they were hired by art director Ed Bell as an intern\, straight out of the science illustration graduate program at U.C. Santa Cruz. With a double major in geology and studio art from Smith College\, Jen started as an assistant art director and later moved on to work for National Geographic magazine as a hybrid assistant art director/researcher and then as a designer.
URL:https://brown.columbia.edu/event/lectures-in-dataviz-jchristiansen/
LOCATION:Brown Institute at Columbia\, 2950 Broadway\, New York\, NY\, 10027\, United States
CATEGORIES:Lectures in Data Visualization
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