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DTSTART;TZID=America/New_York:20230504T120000
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SUMMARY:Lectures in Data Visualization: Gurman Bhatia
DESCRIPTION:The 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. \nRegister to Attend \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\nGurman Bhatia is an independent information designer\, developer and award-winning data journalist based in New Delhi\, India. For the past seven years\, Bhatia has been using data\, visuals and code to craft narratives at local\, national\, international news outlets and non-profit organisations. She is extremely passionate about data communication and journalism – things she often discusses on Twitter. \nBhatia has spent six years in newsrooms such as Reuters in Singapore\, the Hindustan Times in Delhi\, and the Palm Beach Post and Milwaukee Journal Sentinel in the United States before going independent in 2021. Since then\, she has trained over 750 people in data journalism and/or visualisation and helped several non-profit organisations communicate their data-driven research better.\nA self-taught coder and designer\, I hold a Masters in Journalism from Columbia University\, New York. My work has won several awards internationally\, including the Online News Association Awards\, Malofiej Infographic Summit Awards\, The Webby Awards and GEN Data Journalism Awards.
URL:https://brown.stanford.edu/event/lectures-in-dataviz-gbhatia/
LOCATION:Brown Institute at Columbia\, 2950 Broadway\, New York\, NY\, 10027\, United States
CATEGORIES:Lectures in Data Visualization
ATTACH;FMTTYPE=image/jpeg:https://brown.stanford.edu/wp-content/uploads/2023/02/Artboard-1-copy-10-100.jpg
ORGANIZER;CN="Brown Institute @ Columbia":MAILTO:browninstitute@columbia.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230420T120000
DTEND;TZID=America/New_York:20230420T133000
DTSTAMP:20260415T134852
CREATED:20230228T140041Z
LAST-MODIFIED:20230228T141914Z
UID:8272-1681992000-1681997400@brown.stanford.edu
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.stanford.edu/event/lectures-in-dataviz-jchristiansen/
LOCATION:Brown Institute at Columbia\, 2950 Broadway\, New York\, NY\, 10027\, United States
CATEGORIES:Lectures in Data Visualization
ATTACH;FMTTYPE=image/jpeg:https://brown.stanford.edu/wp-content/uploads/2023/02/Artboard-1-copy-9-100.jpg
ORGANIZER;CN="Brown Institute @ Columbia":MAILTO:browninstitute@columbia.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230406T120000
DTEND;TZID=America/New_York:20230406T133000
DTSTAMP:20260415T134852
CREATED:20230228T140026Z
LAST-MODIFIED:20230328T134737Z
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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.stanford.edu/event/lectures-in-dataviz-asatyanarayan/
LOCATION:Brown Institute at Columbia\, 2950 Broadway\, New York\, NY\, 10027\, United States
CATEGORIES:Lectures in Data Visualization
ATTACH;FMTTYPE=image/jpeg:https://brown.stanford.edu/wp-content/uploads/2023/02/Artboard-1-copy-8-100.jpg
ORGANIZER;CN="Brown Institute @ Columbia":MAILTO:browninstitute@columbia.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230323T120000
DTEND;TZID=America/New_York:20230323T133000
DTSTAMP:20260415T134852
CREATED:20230228T140017Z
LAST-MODIFIED:20230320T182154Z
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SUMMARY:Lectures in Data Visualization: Dominik Moritz\, Carnegie Mellon University
DESCRIPTION:The future of Data Science is Live and in the Browser \nData science is a constantly evolving field\, and as such\, it is important to continually explore new ideas for improving the tools we use. In this talk\, I will talk about two ideas that may change how and where we build these tools. \nFirst\, I will argue that data science should be interactive and live\, with no wait time for changing filters or updating parameters. Slow analysis has been shown to have disadvantages and even dangers\, yet few tools have been able to provide both a seamless user experience and the necessary performance. We will explore how web developers have already achieved this level of interactivity and demonstrate how the same experience should be and can be delivered to data workers. \nSecond\, we will examine how the browser is already how that data scientists access many tools\, such as Jupyter and ChatGPT. However\, delays caused by network connections create new challenges for tool builders. We will explore the opportunities that new technologies like WebAssembly\, WebGPU\, and Apache Arrow offer for analysis and machine learning completely in the browser. \nRegister to Attend \n\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. \n  \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 \nDominik Moritz is on the faculty at Carnegie Mellon University where he co-directs the Data Interaction Group (https://dig.cmu.edu/) at the Human-Computer Interaction Institute. His group’s research develops interactive systems that empower everyone to effectively analyze and communicate data. Dominik also manages the visualization team in Apple’s machine learning organization. His systems (Vega-Lite\, Falcon\, Draco\, Voyager\, and others) have won awards at academic venues (e.g. IEEE VIS and CHI)\, are widely used in industry\, and by the Python and JavaScript data science communities. Dominik got his PhD from the Paul G. Allen School at the University of Washington\, where he was advised by Jeff Heer and Bill Howe.
URL:https://brown.stanford.edu/event/dom-moritz/
LOCATION:Brown Institute at Columbia\, 2950 Broadway\, New York\, NY\, 10027\, United States
CATEGORIES:Lectures in Data Visualization
ATTACH;FMTTYPE=image/jpeg:https://brown.stanford.edu/wp-content/uploads/2023/02/Artboard-1-copy-13-100.jpg
ORGANIZER;CN="Brown Institute @ Columbia":MAILTO:browninstitute@columbia.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230309T120000
DTEND;TZID=America/New_York:20230309T133000
DTSTAMP:20260415T134852
CREATED:20230228T140025Z
LAST-MODIFIED:20230228T141948Z
UID:8238-1678363200-1678368600@brown.stanford.edu
SUMMARY:Lectures in Data Visualization: Cindy Xiong\, UMass Amherst
DESCRIPTION:Designs to Support Better Visual Data Communication\nCindy Xiong\, UMass Amherst\n \nWell-chosen data visualizations can lead to powerful and intuitive processing by a viewer\, both for visual analytics and data storytelling. When badly chosen\, visualizations leave important patterns opaque or misunderstood. So how can we design an effective visualization? I will share several empirical studies demonstrating that visualization design can influence viewer perception and interpretation of data\, referencing methods and insights from cognitive psychology. I leverage these study results to design natural language interfaces that recommend the most effective visualization to answer user queries and help them extract the ‘right’ message from data. I then identify two challenges in developing such an interface. First\, human perception and interpretation of visualizations is riddled with biases\, so we need to understand how people extract information from data. Second\, natural language queries describing takeaways from visualizations can be ambiguous and thus difficult to interpret and model\, so we need to investigate how people use natural language to describe a specific message. I will discuss ongoing and future efforts to address these challenges\, providing concrete guidelines for visualization tools that help people more effectively explore and communicate data. \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 \nCindy Xiong is an Assistant Professor in the College of Information and Computer Sciences at the University of Massachusetts Amherst. She received her Ph.D. in Cognitive Psychology and her MS in Statistics from Northwestern University. Her research at the intersection of human perception\, cognition\, and data visualization has received awards at premier venues in psychology and computer science\, including ACM CHI\, Psychonomics\, IEEE VIS\, and IEEE VGTC. She is also one of the founding leaders of VISxVISION (visxvision.com)\, an initiative dedicated to increasing collaboration between visualization researchers and perceptual + cognitive psychologists.
URL:https://brown.stanford.edu/event/lectures-in-data-visualization-cindy-xiong-umass-amherst/
LOCATION:Brown Institute at Columbia\, 2950 Broadway\, New York\, NY\, 10027\, United States
CATEGORIES:Lectures in Data Visualization
ATTACH;FMTTYPE=image/jpeg:https://brown.stanford.edu/wp-content/uploads/2023/03/Artboard-1-copy-12-100.jpg
ORGANIZER;CN="Brown Institute @ Columbia":MAILTO:browninstitute@columbia.edu
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