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Events for November 15, 2016

  • USC Stem Cell Seminar: Nicholas Baker, Albert Einstein College of Medicine

    Tue, Nov 15, 2016 @ 11:00 AM - 12:00 PM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars

    Speaker: Nicholas Baker, Albert Einstein College of Medicine

    Talk Title: TBD

    Series: Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at USC Distinguished Speakers Series

    Host: USC Stem Cell

    More Info: http://stemcell.usc.edu/events

    Webcast: http://keckmedia.usc.edu/Mediasite/Catalog/catalogs/StemCellSeminar

    Location: Eli & Edythe Broad CIRM Center for Regenerative Medicine & Stem Cell Resch. (BCC) - First Floor Conference Room

    WebCast Link: http://keckmedia.usc.edu/Mediasite/Catalog/catalogs/StemCellSeminar

    Audiences: Everyone Is Invited

    Contact: Cristy Lytal/USC Stem Cell

    Event Link: http://stemcell.usc.edu/events

  • CS Colloquium and RASC Seminar: Subramanian Ramamoorthy (University of Edinburgh) -Representations and Models for Collaboratively Intelligent Robots

    Tue, Nov 15, 2016 @ 03:30 PM - 05:00 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars

    Speaker: Subramanian Ramamoorthy, University of Edinburgh

    Talk Title: Representations and Models for Collaboratively Intelligent Robots

    Series: RASC Seminar Series

    Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.

    We are motivated by the problem of building autonomous robots that are able to work collaboratively with other agents, such as human co-workers. One key attribute of such an autonomous system is the ability to make predictions about the actions and intentions of other agents in a dynamic environment - both to interpret the activity context as it is being played out and to adapt actions in response to that contextual information.

    Drawing on examples from robotic systems we have developed in my lab, including mobile robots that can navigate effectively in crowded spaces and humanoid robots that can cooperate in assembly tasks, I will present recent results addressing the questions of how to efficiently capture the hierarchical nature of activities, and how to rapidly estimate latent factors, such as hidden goals and intent.

    Firstly, I will describe a procedure for topological trajectory classification, using the concept of persistent homology, which enables unsupervised extraction of certain kinds of relational concepts in motion data. One use of this representation is in devising a multi-scale version of Bayesian recursive estimation, which is a step towards reliably grounding human instructions in the realized activity.

    Finally, I will describe work with a human-robot interface based on the combined use of vision and mobile 3D eye tracking as a signal for inference about fixation programs. Formulating this in terms of a probabilistic generative model, we estimate fixation locations within a 3D scene, which in turn allows us to associate symbols in a higher level plan with the actual appearance of novel objects that the symbols refer to.

    Biography: Dr. Subramanian Ramamoorthy is a Reader (Associate Professor) in the School of Informatics, University of Edinburgh, where he has been on the faculty since 2007. He is a Coordinator of the EPSRC Robotarium Research Facility in the School of Informatics, and Executive Committee Member for Edinburgh Centre for Robotics. He received his PhD in Electrical and Computer Engineering from The University of Texas at Austin in 2007. He is an elected Member of the Young Academy of Scotland at the Royal Society of Edinburgh, and has held Visiting Professor positions at the Precourt Institute for Energy at Stanford University and at the University of Rome "La Sapienza".

    His research focus has been on robot learning and decision-making under uncertainty, with emphasis on problems involving human-robot and multi-robot collaborative activities. These problems are solved using a combination machine learning techniques with emphasis on issues of transfer, online and reinforcement learning as well as new representations and analysis techniques based on geometric/topological abstractions.

    His work has been recognised by nominations for Best Paper Awards at major international conferences - ICRA 2008, IROS 2010, ICDL 2012 and EACL 2014. He serves in editorial and programme committee roles for conferences and journals in the areas of AI and Robotics. He leads Team Edinferno, the first UK entry in the Standard Platform League at the RoboCup International Competition. This work has received media coverage, including by BBC News and The Telegraph, and has resulted in many public engagement activities, such as at the Royal Society Summer Science Exhibition, Edinburgh International Science festival and Edinburgh Festival Fringe.
    Before joining the School of Informatics, he was a Staff Engineer with National Instruments Corp., where he contributed to five products in the areas of motion control, computer vision and dynamic simulation. This work resulted in seven US patents and numerous industry awards for product innovation.

    Host: Gaurav Sukhatme

    Location: Henry Salvatori Computer Science Center (SAL) - 101

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair