PhD Student
Computer Science
1148 Kelley Engineering Center
Corvallis, OR 97331-5501
 

Education

  • H.B.S. Mathematical Science, Oregon State University (2010)
  • H.B.S. Computer Science, Oregon State University (2010)
  • M.S. Computer Science, Oregon State University (2013)

Major Professor(s)

Publications

  • Moore, T. and Wong, W-K. (2018). An Efficient Quantile Spatial Scan Statistic for Finding Unusual Regions in Continuous Spatial Data with Covariates. UAI. Code available at https://github.com/moortrav/QSSS
  • Kelling, S., Johnston, A., Hochachka, W. M., Iliff, M., Fink, D., Gerbracht, J., Lagoze, C., La Sorte, F. A., Moore, T., Wiggins, A., Wong, W-K., Wood, C. and Yu, J. (2015). Can Observation Skills of Citizen Scientists Be Estimated Using Species Accumulation Curves? PLoS ONE, 10(10): e0139600. doi:10.1371/journal.pone.0139600.
  • Moore, T. and Wong, W-K. (2015). Discovering Hotspots and Coldspots of Species Richness in eBird Data. In AAAI Workshop: Computational Sustainability.
    Das, S., Moore, T., Wong, W-K., Stumpf, S., Oberst, I., McIntosh, K. and Burnett, M. (2013). End-user feature labeling: Supervised and semi-supervised approaches based on locally-weighted logistic regression. Artificial Intelligence, 204:56-74.
  • Curran, W., Moore, T., Kulesza, T., Wong, W-K., Todorovic, S., Stumpf, S., White, R., and Burnett, M. (2012). Towards Recognizing "Cool": Can End Users Help Computer Vision Recognize Subjective Attributes of Objects in Images? Proceedings of the 2012 International Conference on Intelligent User Interfaces, (pp. 285-288), New York, NY: ACM Press.
  • Wong, W-K., Oberst, I., Das, S., Moore, T., Stumpf, S., McIntosh, K., and Burnett, M. (2011). End-User Feature Labeling via Locally Weighted Logistic Regression. Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, (pp. 1575-1578).
  • Wong, W-K., Oberst, I., Das, S., Moore, T., Stumpf, S., McIntosh, K., and Burnett, M. (2011). End-User Feature Labeling: A Locally-Weighted Regression Approach. ACM International Conference on Intelligent User Interfaces, (pp. 115-124), New York, NY: ACM Press. Best Paper Nomination at IUI 2011.
  • Kulesza, T., Stumpf, S., Burnett, M., Wong, W-K., Riche, Y., Moore, T., Oberst, I., Shinsel, A., and McIntosh, K. Explanatory Debugging: Supporting End-User Debugging of Machine-Learned Programs. (2010). In Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing 2010, (pp. 41-48).