Daniel L. Ong

I am a recent graduate in Computer Science from the University of California at Berkeley. Since Spring 2003, I have been fortunate to work with Stuart Russell and the First Order Probabilistic Language group on efficient representation and inference of knowledge.

As an undergraduate, I have been a Computer Science tutor at the Student Learning Center, the main academic support center on campus. I was also the founding Director of the Mentoring Program at the Computer Science Undergraduate Association, and continue to provide direction to the program in my spare time.

I have been working on the Bayesian Logic (BLOG) project with Stuart Russell and the First-Order Probabilistic Logic (FOPL) group. Our latest paper introduces BLOG, our formal FOPL language, and will be presented at the Nineteenth International Joint Conference on Artificial Intelligence (Edinburgh, Scotland):
Brian Milch, Bhaskara Marthi, Stuart Russell, David Sontag, Daniel L. Ong, and Andrey Kolobov. "BLOG: Probabilistic Models with Unknown Objects." IJCAI 2005.
Our theoretical findings so far have been presented as a paper at the Tenth International Workshop on Artificial Intelligence and Statistics (Hastings, Barbados):
Brian Milch, Bhaskara Marthi, David Sontag, Stuart Russell, Daniel L. Ong, and Andrey Kolobov. "Approximate Inference for Infinite Contingent Bayesian Networks." AISTATS 2005. [pdf]
Prediction of Structural RNA Genes through Computational Phylogenetic Shadowing: a project for CS 281A (Statistical Learning Theory: Graphical Models) outlining an approach to classifying RNA genes, done jointly with Kushal Chakrabarti. [paper] [poster]
This work was also presented as a poster in the Eighth Annual International Conference in Research in Computational Mollecular Biology (San Diego, CA):
Kushal Chakrabarti and Daniel L. Ong. "Computational Identification of Noncoding RNA Genes through Phylogenetic Shadowing." ACM/ISCB RECOMB 2004. [abstract]