The Rochester Big Data Initiative fosters research and collaboration across the university in computational, data-intensive science.
Global-scale behavior and health tracking and prediction using social media.
Knowledge representation and reasoning combining first-order logic and probabilty theory for activity and plan recognition.
Proactive memory and problem solving aids that help an individual perform the tasks of day-to-day life.
Developing the next generation of pervasive computing systems.
Integrating language and machine vision for learning complex tasks by demostration. Joint project with James Allen.
Project ACCESS: Assisted Cognition in Community, Employment and Support Settings
Opportunity Knocks: A Personal Guidance System
Cachet: Model counting using component caching and clause learning
Sensing and Modeling Dynamic Social Networks
CORE: Computational Principles for Optimization of Resources and Execution Time
Provably Reliable Question-Answering Interfaces: the precursor to KnowItAll
ReferralWeb, a system for finding and searching social networks on the World Wide Web
Planning as Satisfiability: the SatPlan and Blackbox planning systems
Walksat and GSAT, SAT solvers using local search. For more SAT information, see Sat-Ex and SatLive!
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