Logo: University of Southern California

Events Calendar



Select a calendar:



Filter February Events by Event Type:



Events for February 28, 2017

  • USC Stem Cell Seminar: Michael Rudnicki, Ottawa Hospital Research Institute

    USC Stem Cell Seminar: Michael Rudnicki, Ottawa Hospital Research Institute

    Tue, Feb 28, 2017 @ 11:00 AM - 12:00 PM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Michael Rudnicki, Ottawa Hospital Research Institute

    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/stem-cell-seminar

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

    WebCast Link: http://keckmedia.usc.edu/stem-cell-seminar

    Audiences: Everyone Is Invited

    Contact: Cristy Lytal/USC Stem Cell

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

    Add to Google CalendarDownload ICS File for OutlookDownload iCal File
  • CS Colloquium: Vinodkumar Prabhakaran (Stanford University) - NLP for Social Good: Inferring Social Context from Language

    Tue, Feb 28, 2017 @ 11:00 AM - 12:20 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Vinodkumar Prabhakaran, Stanford University

    Talk Title: NLP for Social Good: Inferring Social Context from Language

    Series: CS Colloquium

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

    The vast quantities of language data online and offline offer tremendous opportunities to study society through language. In this talk, I show how natural language processing techniques can be expanded from understanding the meanings of words and sentences, to inferring the underlying social structures and processes they reflect and identifying crucial shortcomings in them. I apply these techniques to computationally detect two ways in which the social context affects the use of language: social relations affecting how people interact with one another, and social constructs shaping how institutions interact with communities. In the first part, I show how to computationally detect manifestations of social power in workplace interactions between individuals -” providing means for organizations to detect incivility at workplace. In the second part, I show how to computationally investigate the ways race shapes the interactions between the police and the communities they serve -” providing means for departments to address and monitor racial disparities in policing. My research looks beyond words and phrases, and introduce ways to infer richer rhetorical and dialog information like conversational structure and respect that reflect the social context, demonstrating the importance of deeper language processing for the computational social sciences.

    Biography: Vinodkumar Prabhakaran is a postdoctoral fellow in the computer science department at Stanford University. His research falls in the inter-disciplinary field of computational sociolinguistics, in which he builds and uses computational tools to analyze linguistic patterns that reveal the underlying social contexts in which language is used. He received his PhD in Computer Science from Columbia University in 2015. In his doctoral thesis, he studied how machine learning and natural language processing techniques can help detect the underlying social power structures that guide social interactions. As part of his research, he has also made significant contributions to core NLP problems such as extracting information from text, as well as modeling structures of dialog and discourse.

    Host: CS Department

    Location: Ronald Tutor Hall of Engineering (RTH) - 217

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

    Add to Google CalendarDownload ICS File for OutlookDownload iCal File
  • Epstein Institute Seminar, ISE 651

    Tue, Feb 28, 2017 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Mariel Lavieri , Associate Professor, University of Michigan

    Talk Title: Personalizing Management of Glaucoma Patients

    Host: Dr. Sze-chuan Suen

    More Information: February 28, 2017_Lavieri.pdf

    Location: Ethel Percy Andrus Gerontology Center (GER) - 206

    Audiences: Everyone Is Invited

    Contact: Grace Owh

    Add to Google CalendarDownload ICS File for OutlookDownload iCal File
  • CS Colloquium: Fan Long (MIT CSAIL) - Learning How to Patch Software Errors Automatically

    Tue, Feb 28, 2017 @ 04:00 PM - 05:00 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Fan Long, MIT CSAIL

    Talk Title: Learning How to Patch Software Errors Automatically

    Series: CS Colloquium

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

    Software systems are increasingly integrated into every part of our society. As the number of systems and our dependence on these systems continue to grow, making these systems reliable and secure becomes an increasingly important challenge for our society and a daunting task for software developers.

    Automatic patch generation holds out the promise of automatically correcting software defects without the need for developers to manually diagnose, understand, and correct these defects. In this talk, I will present two novel automatic patch generation systems, Prophet and Genesis, both of which learn from past successful human patches to automatically fix defects. By collectively leveraging development efforts worldwide, Prophet and Genesis automatically generate correct patches for real-world defects in large open-source C and Java applications with up to millions lines of code. This research also demonstrates that the growing volume of software programs is not just a challenge but also a great opportunity. Exploiting this opportunity can enable revolutionary new automated techniques that enhance software reliability and security.

    Biography: Fan Long is a PhD candidate in Computer Science at Massachusetts Institute of Technology (MIT). His research to date has focused on developing automated programming systems to improve software reliability and security. He has developed systems that automatically identify and eliminate errors in large software programs and systems that enable software programs to operate successfully in spite of the presence of errors. He holds a BE from Tsinghua University and a MS from MIT.


    Host: CS Department

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

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

    Add to Google CalendarDownload ICS File for OutlookDownload iCal File