University of Texas at Austin
McCombs School of Business McCombs School of Business

Sinead Williamson

Assistant Professor

Department: Information, Risk, and Operations Mgmt.

Contact Information

CBA 5.202

Biography Sinead received her MEng from the University of Oxford, MSc from University College London, and PhD from the University of Cambridge. Her main research areas are Bayesian nonparametric statistics and machine learning. Before joining the faculty at UT Austin, Sinead was a Post Doc at Carnegie Mellon University.
Sinead Williamson, Michael Minyi Zhang, and Paul Damien. 2020. A New Class of Time Dependent Latent Factor Models with Applications. Journal of Machine Learning Research 21(26-47), 1-24.
Michael Minyi Zhang and Sinead Williamson. 2019. Embarrassingly Parallel Inference for Gaussian Processes. Journal of Machine Learning Research 20(161-84), 1-26.
Markus Peters, Maytal Saar-Tsechansky, Wolfgang Ketter, Sinead Williamson, Perry Groot, and Tom Heskes. 2018. A Scalable Preference Model for Autonomous Decision-Making. Machine Learning 107(6), 1039-1068.
Nicholas J. Foti and Sinead Williamson. 2015. A Survey of Non-Exchangeable Priors for Bayesian Nonparametric Models. IEEE Transactions on Pattern Analysis & Machine Intelligence 37(2), 359-371.
A. Dubey, A. Hefny, Sinead Williamson, and E. P. Xing. 2013. A Non-Parametric Mixture Model for Topic Modeling Over Time. SDM 13:530-538.
N. Foti, J. Futoma, D. Rockmore, and Sinead Williamson. 2013. A Unifying Representation for a Class of Complete Measures. AISTATS, JMLF W&CP 31:20-28.
Sinead Williamson, A. Dubey, and E. P. Xing. 2013. Parallel Markov Chain Monte Carlo for Nonparametric Mixture Models. ICML, JMLR W&CP 28(1):98-106.
Y. Hu, K. Zhai, Sinead Williamson, and J. Boyd-Graber. 2012. Modeling Images Using Transformed Indian Buffet Processes. ICML 29:1511-1518.
N. Foti and Sinead Williamson. 2012. Slice Sampling Normalized Kernel-Weighted Completely Random Measure Mixture Models. NIPS 25:2249-2257.
Sinead Williamson, P. Orbanz, and Z. Ghahramani. 2010. Dependent Indian Buffet Processes. AISTATS, JMLR W&CP 9:924-931.
Sinead Williamson, C. Wang, K. A. Heller, and D. M. Blei. 2010. The IBP-Compound Dirichlet Process and its Application to Focused Topic Modeling. ICML 27:1151-1158.
K. A. Heller, Sinead Williamson, and Z. Ghahramani. 2008. Statistical Models for Partial Membership. ICML 25:392-399.
Show all publications