Juho Kim

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Ph.D. candidate @ MIT CSAIL

Curriculum Vitae

@imjuhokim on Twitter
mcpanic.com (blog in Korean)

Last update: Feb. 10, 2014
I'm a fourth-year Ph.D. candidate in EECS at MIT, focusing on Human-Computer Interaction (HCI) research. I work in the User Interface Design Group in CSAIL (Computer Science and Artificial Intelligence Laboratory), advised by Prof. Rob Miller and Prof. Krzysztof Gajos. The Samsung Fellowship is supporting my graduate studies for 7 years.

I design interactive technologies that leverage collective learner activities to enhance the video learning experience. Millions of learners today are using educational videos to master skills and take classes from online platforms such as YouTube, Coursera, or edX. Massive data from learner activities provides an unprecedented opportunity to enable more interactive and constructive video learning. My research introduces learnersourcing, a set of methods and tools that collect, process, and visualize large-scale learner activities.

I am interested in applying established learning theories beyond small, in-person classrooms. My approach combines a) crowdsourcing to collect and handle a large amount of learner input, b) social computing to incentivize learners through collaboration, and c) content-based video analysis techniques such as computer vision and natural language processing to complement learner input.
Current Projects

ToolScape: Enhancing How-to Videos

ToolScape captures work-in-progress images and step-by-step information inside video tutorials to support learning new skills in Photoshop. It features workflows to capture annotations from crowd workers, or learners watching the same video.

Cobi: Communitysourcing Large-Scale Conference Scheduling

Cobi integrates community process, constraint-solving intelligence, and end-user interface to help in the schedule process of large conferences.

TalkScape: Lecture Annotation Tool

How can we capture, interact with, and discuss important moments in a presentation or lecture video? TalkScape supports taking annotated snapshots, visualizing an outline, and deep-linking between the video and external resources.