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PEOPLE:
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- interface between planning and control, as well as the control and coordination of large-scale distributed, networked, embedded systems
- simulation, robotics, learning control, biologically inspired control
- Ph.D. in Biophysics & M.S. in Electrical Engineering, U.C. Berkeley; A.B. in Physics, Harvard
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- applies AI planning & KR to real-world problems
- semantic workflows, cognitive robotics, ubicomp
- specializes highly dynamic, open-world environments
- Ph.D., University of Toronto
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- software developer
- led the development of the Diagnostic Competition Framework at NASA
- software used successfully in PHM Society's International Diagnostic Competition
- B.S., Mathematics, Santa Clara University; working on M.S., Computer Science, Stanford University
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- directs artificial intelligence and predictive analytics focused on the enterprise
- anomaly and fraud detection, contextual intelligence, recommendation systems, and tools for smart organizations
- developing rich, predictive user models
- M.S. in Computer Science from Stanford University; M.S. in Cognitive Psychology from the University of Dayton; B.S. in Psychology from Otterbein College
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- modeling complex business processes for decision support system
- relevance-based document retrieval from personal library
- usability of large software systems
- M.S., Software Engineering, Carnegie Mellon University
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- heuristic search, packing, constraint satisfaction, planning, scheduling
- Ph.D., Computer Science, UCLA
- former Micro Fellow and EGSA Angels Fellow
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- produces software for various embedded reasoning systems projects
- was computer scientist at NASA Ames Reserach Center & SRI International
- developed intelligent software leveraging automated planning and scheduling for various applications
- Ph.D., Artificial Intelligence
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- qualitative reasoning, machine learning, planning, intelligent agents, spatial reasoning
- worked in U.S. Naval Research Laboratory
- Ph.D., Northwestern University EECS
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- design and development of complex systems
- engineering design automation and optimization
- prognostic and health management, model-based systems, automated reasoning, knowledge and information management, risk and reliability-based design
- previously at NASA Ames Research Center and Dell Corporation
- PhD, UT Austin, MS, Carnegie Mellon University, Mechanical Engineering
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- signal processing, statistical modeling and inference, distributed sensor networks
- applications such as intelligent transportation systems
- Ph.D., M.S. Electrical Engineering from the University of Illinois at Urbana-Champaign
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- control, optimization, networked dynamics systems, robotics, and flight dynamics, in energy, transportation, multi-agent system, and healthcare
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Ph.D. in Aeronautics and Astronautics and M.Sc. in Mathematics from University of Washington
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- inference, tracking, learning, and planning applications for government and industry clients
- model-based control on a system for improving the diagnostic information generated from automatically constructed plans; machine learning of rules to diagnose problems in printing engines from fault code sequences; and optimization of power loads on aircraft to minimize power and cost and maximize utility
- Ph.D. in Computer Science from the University of British Columbia
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- fleet health management, diagnostics and prognostics, electromechanical systems, sensors
- modeling, dynamics, pattern recognition and signal processing, piezoelectric transducers, wave propagation, guided-wave structural health monitoring
- Ph.D., M.S., Aerospace Engineering, University of Michigan, Ann Arbor; B.S., Mechanical Engineering, IIT Bombay
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- Big Data
- Clean Water
- Cleantech and Energy
- Content-Centric Networking
- Contextual Intelligence
- Design and Digital Manufacturing
- Health and Wellness
- Innovation Services
- Intelligent Automation
- Optoelectronics and Optics
- Printed and Flexible Electronics