Ashish Sabharwal

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Ashish Sabharwal, an Indian American mathematician, computer scientist, and senior research scientist at the Allen Institute for Artificial Intelligence (AI2), exploring new avenues in probabilistic inference, combinatorial reasoning, and discrete optimization. Before, he spent at Thomas J. Watson Research Center and Cornell University. He defended his Ph.D. in 2005 from University of Washington, Seattle on algorithmic applications of propositional proof complexity, SAT solvers, after graduating from the Indian Institute of Technology, Kanpur. Along with Raghuram Ramanujan and Bart Selman, Ashish Sabharwal researched on properties of adversarial search spaces that play a key role in the success or failure of UCT and similar sampling-based approaches.

=Selected Publications=

2005 ...

 * Ashish Sabharwal (2005). Algorithmic Applications of Propositional Proof Complexity. Ph.D. thesis, University of Washington, pdf
 * Carla P. Gomes, Ashish Sabharwal, Bart Selman (2006). Model Counting: A New Strategy for Obtaining Good Bounds. AAAI 2006, pdf, slides as pdf
 * Lukas Kroc, Ashish Sabharwal, Bart Selman (2008, 2011). Leveraging Belief Propagation, Backtrack Search, and Statistics for Model Counting. CPAIOR 2008, Annals of Operations Research, Vol. 184

2010 ...

 * Raghuram Ramanujan, Ashish Sabharwal, Bart Selman (2010). On Adversarial Search Spaces and Sampling-Based Planning. ICAPS 2010
 * Ashish Sabharwal, Horst Samulowitz, Chandra Reddy (2012). Guiding Combinatorial Optimization with UCT. CPAIOR 2012, abstract as pdf, draft as pdf
 * Raghuram Ramanujan, Ashish Sabharwal, Bart Selman (2012). Understanding Sampling Style Adversarial Search Methods. arXiv:1203.4011
 * Ashish Sabharwal, Horst Samulowitz (2014). Insights into Parallelism with Intensive Knowledge Sharing. CP 2014, pdf

=External Links=
 * Ashish Sabharwal
 * Ashish Sabharwal's Homepage at Cornell University
 * Ashish Sabharwal - Google Scholar Citations
 * The Mathematics Genealogy Project - Ashish Sabharwal

=References=

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