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Welcome to the Distributed Cognition and Human-Computer Interaction Laboratory, Department of Cognitive Science, University of California, San Diego. The Dcog-HCI Lab is directed by Professors Jim Hollan and Ed Hutchins

Currently there is a shift in cognitive science toward a view of cognition as a property of systems that are larger than isolated individuals. This extends the reach of cognition to encompass interactions between people as well as interactions with resources in the environment. Members of the Dcog-HCI lab are dedicated to developing the theoretical and methodological foundations engendered by this broader view of cognition and interaction. 

We are united in the belief that distributed cognition promises to be a particularly fertile framework for designing and evaluating augmented environments and digital artifacts. A central image for us is environments in which people pursue their activities in collaboration with the elements of of the social and material world. Our core research efforts are directed at understanding such environments: what we really do in them, how we coordinated our activity in them, and what role technology should play in them.

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DCog-HCI (see all)

Lab Meeting-Open

Wed, Feb 1st, 10:10am-11:10am (SSRB 100)
(2 days, 23 hours from now)


Lab Meeting-Open

Wed, Feb 8th, 10:10am-11:10am (SSRB 100)
(1 week, 2 days from now)


Lab Meeting-Ryan Kastner

Wed, Feb 15th, 10:10am-11:10am (SSRB 100)
(2 weeks, 2 days from now)


Lab Meeting-Open

Wed, Feb 22nd, 10:10am-11:10am (SSRB 100)
(3 weeks, 2 days from now)


Lab Meeting-Nadir Weibel

Wed, Feb 29th, 10:10am-11:10am (SSRB 100)
(1 month from now)


Lab Meeting-Terry Jernigan

Wed, Mar 7th, 10:10am-11:10am (SSRB 100)
(1 month, 1 week from now)


Lab Meeting-Ed &Team on ETRA

Wed, Mar 14th, 10:10am-11:10am (SSRB 100)
(1 month, 2 weeks from now)


UCSD (see all)

Andrew Ng (CSE talk)

Machine learning and AI via large scale brain simulations

By building large-scale simulations of cortical (brain) computations, can
we enable revolutionary progress in AI and machine learning? Machine
learning often works very well, but can be a lot of work to apply because
it requires spending a long time engineering the input representation (or
"features") for each specific problem. This is true for machine learning
applications in vision, audio, text/NLP and other problems.
To address this, researchers have recently ...
(click for details)

Mon, Jan 30th, 11:00am-12:00pm (EBU3B, Room 1202)
(23 hours, 55 minutes from now)


Scott Grafton (CNS talk)

Motor Simulation, Emulation & Imagery: When does the motor system solve
problems of cognition?

Rapid advances in brain-machine interfaces, the application of
machine learning algorithms and efforts to augment human performance demand
a deeper understanding of the structure of goal directed information being
derived from the human motor system. This talk considers alternative
accounts of motor related information and asks whether simulation within
the motor system is used to solve problems of perception and cognition. New
behavioral studies highlight ...
(click for details)

Tue, Jan 31st, 12:00pm-1:00pm (Mandler 3545 (Crick Conference Room))
(2 days from now)