Christopher H. Lin (林懷璿)
MS, Computer Science & Engineering, University of Washington, March 2013
BA, Computer Science, Mathematics, UC Berkeley, May 2011

About Me

Image of Christopher H. Lin I am a PhD student in Computer Science and Engineering at the University of Washington, advised by Dan Weld and Mausam. My research interests span Artificial Intelligence, Natural Language Processing, and Crowdsourcing. The bulk of my work focuses on the intelligent management of learning (as opposed to the learning itself), and ranges from POMDP methods for test set construction via crowdsourcing, to algorithms that achieve faster and cheaper learning by trading off between diverse and focused training examples. To show that my ideas work in practice, I like to use natural language domains like information extraction and entity linking as testbeds, and I am particularly excited about how my ideas can be applied to creating next-generation conversational agents. Here is a video of a short talk I gave (last 5 minutes of the video), in which I describe my research at a high level.

In my free time, I play the violin. I currently play with the Seattle Philharmonic. I'm also a member of the Serendipity Quartet, which I formed in late 2015 with several members of the Phil. I most enjoy the works of late romantic/early 20th century Russian and German composers (Tchaikovsky, Rachmaninoff, Shostakovich, Prokofiev, Mahler, R. Strauss, Brahms, etc). Beethoven is also amazing. I've performed Tchaikovsky's 5th in Carnegie Hall under Benjamin Zander, and after experiencing the amazing acoustics, I think that playing/listening inside Carnegie Hall should be on everyone's bucket list.

Teaching

Selected Publications

Please see my Resume/CV for a full list. Here is my Google Scholar page.
  1. Christopher H. Lin, Mausam, and Daniel S. Weld. "Re-active Learning: Active Learning with Relabeling." In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI). Phoenix, Arizona. February 2016.
    Accepted for long oral presentation
    Acceptance rate: 26%
    [PDF] [Supplementary Materials] [Talk]
  2. Christopher H. Lin, Andrey Kolobov, Ece Kamar, and Eric Horvitz. "Metareasoning for Planning Under Uncertainty." In Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI). Buenos Aires, Argentina. July 2015.
    Accepted for long oral presentation
    Acceptance rate: 29%
    [PDF] [PDF (Extended Version)] [Talk]
  3. Christopher H. Lin, Mausam, and Daniel S. Weld. "To Re(label), or Not To Re(label)." In Proceedings of the 2nd AAAI Conference on Human Computation and Crowdsourcing (HCOMP). Pittsburgh, PA, USA. Nov 2014.
    Acceptance rate: 32%
    [PDF] [Talk]
  4. Christopher H. Lin, Ece Kamar, and Eric Horvitz. "Signals in the Silence: Models of Implicit Feedback in a Recommendation System for Crowdsourcing." In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI). Quebec City, Quebec, Canada. July 2014.
    Accepted for both oral and poster presentation
    Acceptance rate: 28%
    [PDF] [Errata] [Talk]
  5. Christopher H. Lin, Mausam, and Daniel S. Weld. "Crowdsourcing Control: Moving Beyond Multiple Choice." In Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence (UAI). Catalina Island, CA, USA. Aug 2012.
    Acceptance rate: 31%
    [PDF] [Supplementary Materials]
  6. Christopher H. Lin, Mausam, and Daniel S. Weld. "Dynamically Switching between Synergistic Workflows for Crowdsourcing." In Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI). Toronto, ON, Canada. July 2012.
    Accepted for both oral and poster presentation
    Acceptance rate: 26%
    [PDF] [Talk]

Contact Me

Email me: %s@cs.washington.edu % 'chrislin'
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Connect with me: View Christopher Lin's profile on LinkedIn
Most recent attempt to be up-to-date: April 29 2016