Lin Liao’s Home Page

I graduated from University of Washington in Aug, 2006 and am working at Google at Kirkland.

During my Ph.D. study, my research was focused on the combination of techniques from artificial intelligence, machine learning, and ubiquitous computing and their application to practical domains, such as human activity recognition and robotics. My advisors were Professor Dieter Fox and Henry Kautz.

Publications:

Ph.D. Thesis: 

  • L. Liao. Location-based Activity Recognition. University of Washington, 2006. (pdf)

Journals and Book Chapters:

  • L. Liao, D. J. Patterson, D. Fox, and H. Kautz. Learning and Inferring Transportation Routines. in Artificial Intelligence, 2007. (pdf)
  • L. Liao, D. Fox, and H. Kautz. Extracting Places and Activities from GPS Traces Using Hierarchical Conditional Random Fields. in International Journal of Robotics Research, 2007. (pdf)
  • L. Liao, D. J. Patterson, D. Fox, and H. Kautz. Building Personal Maps from GPS Data. in New York Academy of Sciences, 2007.
  • D. J. Patterson, L. Liao, H. Kautz, and D. Fox. Pervasive Computing in the Home and Community. Pervasive Computing in Healthcare, 2006. 79-103.
  • D. Fox, J. Hightower, L. Liao, D. Schulz, and G. Borriello. Bayesian Filtering for Location Estimation. IEEE Pervasive Computing, vol. 2, no. 3, IEEE Computer Society Press, July-September 2003.

Conferences:

  • L. Liao, T. Choudhury, D. Fox, and H. Kautz. Training Conditional Random Fields using Virtual Evidence Boosting. in Proceedings of the International Joint Conference on Artifical Intelligence (IJCAI), 2007. (pdf)
  • B. Limketkai, D. Fox, and L. Liao. CRF-filters: Conditional Particle Filters for Sequential State Estimation. in Proceedings of the International Conference on Robotics and Automation, 2007.  (pdf)
  • L. Liao, D. Fox, and H. Kautz. Location-Based Activity Recognition. in Proceedings of the Neural Information Processing Systems (NIPS), 2005. (pdf)
  • E. Horvitz, J. Apacible, R. Sarin, and L. Liao. Prediction, Expectation, and Surprise: Methods, Designs, and Study of a Deployed Traffic Forecasting Service. in Proceedings of the Conference on Uncertainty and Artificial Intelligence (UAI),2005
  • L. Liao, D. Fox, and H. Kautz. Location-Based Activity Recognition using Relational Markov Networks. in Proceedings of the International Joint Conference on Artifical Intelligence (IJCAI), 2005. (pdf)
  • B. Limketkai, L. Liao, and D. Fox. Relational Object Maps for Mobile Robots. in Proceedings of the International Joint Conference on Artifical Intelligence (IJCAI), 2005. (pdf)
  • D. J. Patterson, L. Liao, K. Gajos, M. Collier, N. Livic, K. Olson, S. Wang, D. Fox, and H. Kautz. Opportunity Knocks: a System to Provide Cognitive Assistance with Transportation Services.  in Proceedings of The Sixth International Conference on Ubiquitous Computing (UBICOMP), 2004. (pdf)
  • L. Liao, D. Fox, and H. Kautz. Learning and Inferring Transportation Routines. in Proceedings of AAAI-04 , 2004. Outstanding Paper Award. (pdf)
  • D. Patterson, L. Liao, D. Fox, and H. Kautz. Inferring High-Level Behavior from Low-Level Sensors. in Proceedings of The Fifth International Conference on Ubiquitous Computing (UBICOMP), 2003. (pdf)
  • L. Liao, D. Fox, J. Hightower, H. Kautz and D. Schulz. Voronoi Tracking: Location Estimation Using Sparse and Noisy Sensor Data. in Proceedings of the International Conference on Intelligent Robots and Systems (IROS), 2003. (pdf)

Workshops and Technical Reports:

  • L. Liao. Stock Option Pricing using Bayes Filters. Technical report, 2004. (pdf)
  • D. Fox, J. Hightower, H. Kautz, L. Liao, and D. J. Patterson. Bayesian Techniques for Location Estimation. UbiComp Workshop on Location Estimation (invited), 2003. (pdf)
  • P. Domingos, et al. Research on Statistical Relational Learning at the University of Washington. IJCAI Workshop on Learning Statistical Models from Relational Data, 2003. (pdf)

Do you still remember the dream when you were young?