The last session of the Transparency Series took place last Saturday and featured Craig Silverman, BuzzFeed’s media editor. Silverman has an incredible record of reporting on Twitter and social media platforms generally. During the day-long workshop, he shared his strategies for breaking stories down into “actors, content, behavior, and networks.” His investigative routine when looking
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Becoming more mindful about visual information: A Q&A with Alberto Cairo, author of ‘How Charts Lie’
Alberto Cairo is an associate professor and Knight Chair of Visual Journalism at the University of Miami. He recorded this interview with Alex Calderwood before delivering a lecture about his recently released book How Charts Lie: Getting Smarter about Visual Information. What spurred you to write this book? Have you been thinking about it for
1000 Cut Journey Announces New Partnership with iNK Stories
We are pleased to announce that the team behind 1000 Cut Journey, which was awarded our 2018-19 Flagship Magic Grant, has partnered with acclaimed visual studio iNK Stories, to expand their Virtual Reality (VR) experience. The project is a bi-coastal initiative between Professor Courtney Cogburn’s research group at the Columbia University School of Social Work
Innovating with AI
Medium’s Chief Architect Xiao Ma spoke at Stanford on Nov. 5th asking the question: How does technology reshape content discovery and delivery? He unpacked Medium’s on-point recommendation system, a hybrid model that joins collaborative filtering (“How can we recommend content based on your previous history and people similar to you?”) and content-based filtering (“I don’t
Hansen and Institute Alumni Receive Grant to Support New Curricula on Technology Design
Award from the Public Interest Technology University Network is part of $3 million “Network Challenge” to grow the field of public interest technology. Three Columbia professors working at the intersection of human-computer interaction (HCI) have received a grant from the Public Interest Technology University Network (PITUN) to support creation of new curricula on designing computational technology that
Scene Graph Prediction with Limited Labels
Authors Vincent Chen, Paroma Varma, Ranjay Krishna, Michael Bernstein, Christopher Re, Li Fei-Fei Our semi-supervised method automatically generates probabilistic relationship labels to train any scene graph model. Abstract Visual knowledge bases such as Visual Genome power numerous applications in computer vision, like visual question answering and captioning, but suffer from sparse, incomplete relationships. All scene
Visual Relationships as Functions: Enabling Few-Shot Scene Graph Prediction
Authors Apoorva Dornadula, Austin Narcomey, Ranjay Krishna, Michael Bernstein, Li Fei-Fei We introduce a scene graph approach that formulates predicates as learned functions, which result in an embedding space for objects that is effective for few-shot. Our formulation treats predicates as learned semantic and spatial functions, which are trained within a graph convolution network. First,
A Taxonomy for VR
Eve Weston, CEO and founder of Los-Angeles based VR studio Exelauno told Stanford students that she has developed a way to talk about VR — what she calls a “taxonomy” for VR. This taxonomy unpacks the emotional intensity of the VR experience into its key parts: Narrative (1st person, 2nd person, 3rd person?) Visual Options (Embodied
Office Hours Announced for CJS Students
The Brown Institute is pleased to announce appointment-based office hours for students needing help in all things digital. This includes (but is not limited to) students seeking assistance with data and statistics, visualization, mapping, natural language processing, web products, immersive media, and the Adobe Creative Suite. Please book office hours at brwn.co/office-hours or by using