About Me

I am currently a PhD candidate in Prof. Rina Dechter’s Automated Reasoning group and a Software Engineer at Google working on Personal Search Infrastructure.

I successfully defended my thesis, titled "Advancing Heuristics for Search over Graphical Models", in March 2017 and am currently working on revisions for the final version to be submitted during the Spring 2017 quarter.

Graphical models are a widely used framework for reasoning tasks. I am particularly interested in search-based approaches to inference and developing/improving heuristics for it. I am also interested in exploring different search strategies.

I have worked on exploring the AND/OR Decision Diagram framework for performing inference and evaluating its quality on solving high-treewidth problems with problem specific structures such as determinism and context-specific independence.

I am currently working on different types of dynamic heuristics for AND/OR Branch and Bound. This work aims to find a good tradeoff between heuristic computation and node expansion in AOBB.

Before UC Irvine, I was an undergraduate research assistant in R-LAIR (Riverside Lab for Artificial Intelligence Research) with Prof. Christian Shelton.

I worked on the CTBN-RLE code base. Specifically, I implemented the structure learning component, which learns a Bayesian network and continuous time Bayesian network structure from trajectory data. It seamlessly incorporates any of the inference methods available in CTBN-RLE to handle the case of partially observed trajectories. I also implemented the mean field variational inference algorithm inside CTBN-RLE.

PhD Candidate in Computer Science (September 2010 - now)
Bren School of Information and Computer Sciences, UC Irvine.
MS in Computer Science (September 2010 - December 2012)
Bren School of Information and Computer Sciences, UC Irvine.
BS in Computer Science (September 2006 - June 2010)
Bourns College of Engineering, UC Riverside.
Work Experience
Software Engineer (March 2017 - now)
Google, Mountain View, CA. Personal Search Infrastructure.
Software Engineering Intern (June 2015 - September 2015)
Google, New York, NY. Search Infrastructure.
Software Engineering Intern (June 2014 - September 2014)
Google, Los Angeles, CA. YouTube.
William Lam, Kalev Kask, Rina Dechter, and Javier Larrosa
On the Impact of Subproblem Orderings on Anytime AND/OR Best-First Search for Lower-Bounds.
In Proceedings of ECAI 2016, The Hague, Netherlands, August 2016.
Rina Dechter, Kalev Kask, William Lam, and Javier Larrosa
Look-ahead with Mini-Bucket Heuristics for MPE.
In Proceedings of AAAI 2016, Phoenix, AZ, USA, February 2016.
William Lam, Kalev Kask, and Rina Dechter
Empowering Mini-Bucket in Anytime Heuristic Search with Look-Ahead: Preliminary Evaluation.
In Proceedings of SoCS 2015, Ein Gedi, the Dead Sea, Israel, June 2015.
William Lam, Kalev Kask, Rina Dechter, and Alexander Ihler
Beyond Static Mini-Bucket: Towards Integrating with Iterative Cost-Shifting Based Dynamic Heuristics.
In Proceedings of SoCS 2014 , Prague, Czech Republic, August 2014.
Junkyu Lee, William Lam, and Rina Dechter.
Benchmark on DAOOPT and GUROBI with the PASCAL2 Inference Challenge Problems.
In DISCML 2013 (a workshop of NIPS 2013), Lake Tahoe, NV, USA, December 2013.
William Lam and Rina Dechter.
Empirical Evaluation of AND/OR Multivalued Decision Diagrams for Inference.
In Doctoral Programme of CP 2012, Qu├ębec City, QC, Canada, October 2012.
[pdf | extended version]
E. Busra Celikkaya, Christian R. Shelton, and William Lam.
Factored Filtering of Continuous-Time Systems.
In Proceedings of UAI 2011, Barcelona, Spain, July 2011.
Christian R. Shelton, Yu Fan, William Lam, Joon Lee, and Jing Xu.
Continuous Time Bayesian Network Reasoning and Learning Engine.
In Journal of Machine Learning Research, 11, 1137-1140.