If we knew what it was we were doing, it would not be called research, would it?
-- Albert Einstein

Current Projects

  • Open Information Extraction: Extracting information from natural language text in a domain-independent manner. We hope to push the precision and recall of Textrunner extractor using probabilistic techniques.

  • Formal Inference in Translation Graph: Developing probabilistic inference techniques to formalize inference in translation graphs, a graph that is formed by combining all available dictionaries between all possible languages in the world. An efficient and high quality inference procedure will enable the system to produce good translations from a sense in one language to several languages, even when there is no available dictionary between the exact pair of languages. More details on the Panimages website. A recent paper on this work.

  • Large-scale Probabilistic Planning: Solving large Markov Decision Processes by combining several optimal as well as approximate techniques. We hope to alleviate the memory bottleneck in solving the large MDPs and scale to large, industry sized probabilistic planning problems. Some recent papers on this work: Paper 1 and Paper 2.

    • Past Projects

  • Open Information Extraction over News: A relation-independent question-answering system over thousands of current news articles. We apply Textrunner information extraction technology as well as news-specific heuristics to construct a massive knowledge base of current events. This information can be queried by asking specific questions or by keyword search.

  • Hybridizing Planners: A fast but suboptimal planner may be hybridized with a slow but optimal one to yield a high-quality, anytime planner that solves the problems in intermediate times. We developed HybPlan, a planner that hybridized GPT and MBP for probabilistic planning.

  • Concurrent Probabilistic Temporal Planning: Developing high-quality and efficient techniques to solve MDPs that formulate probabilistic planning problems involving durative and concurrent actions.

    • Publications

    A complete list of publications can be found here.

    Service

  • PC Member: ICAPS'09, IJCAI'09, ICAPS'08, AAAI'08, ICAPS'07, AAAI'05.
  • Reviewer: JAIR, JMLR, AAMAS, IJCAI, NAACL, UbiComp.
  • Tutorial: Probabilistic Temporal Planning at ICAPS'07.
  • Workshop: A Reality Check for Planning and Scheduling Under Uncertainty at ICAPS'08.

    • Presentations in the AI group (grad school times)

    1. Introduction to Semantic Web (Fall 2001)
    2. PGRAPHPLAN : A planner for probabilistic domains (Spring 2002)
    3. Nursebot : Robot assistants for the elderly (Spring 2002)
    4. SPUDD : A planner for probabilistic domains (Fall 2002)
    5. A survey of Relational MDP approaches (Fall 2003)
    6. Introduction to Markov Decision Processes (Fall 2003)
    7. A survey of Hierarchical Reinforcement Learning Techniques (Spring 2005)