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PEOPLE:

 

Danny Bobrow
  • community knowledge sharing systems
  • natural language-based, broad-coverage system for question answering
  • over 100 published papers, books, and issued patents
  • President of AAAI; Editor-in-chief, Artificial Intelligence; ACM and AAAI fellow

 

Lara Crawford
  • 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

 

Christian Fritz
  • applies AI planning & KR to real-world problems
  • semantic workflows, cognitive robotics, ubicomp
  • specializes highly dynamic, open-world environments
  • Ph.D., University of Toronto

 

 

David Garcia
  • software developer on the Innovation, Design & Engineering Analytics (IDEA) team
  • current focus on data analytics and software solutions for healthcare
  • B.S., Mathematics, Santa Clara University; working towards M.S., Computer Science, Stanford University

 

 

 

Leilani Gilpin
  • research interests include algorithms, machine learning, network and systems analysis, and computational geometry
  • currently working on fraud analysis and anomaly detection in healthcare
  • M.S., Computational and Mathematical Engineering, Stanford University; B.S. in Computer Science and in Mathematics (with honors) and a music minor, UC San Diego

 

David Gunning
  • 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

 

John Hanley
  • 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

 

Tomonori Honda
  • broad experience in engineering design and big data modeling, specializing in formalizing design theory for complex systems
  • researches design for system reliability, prognosis, and maintenance scheduling; design synthesis for complex multidisciplinary systems; and behavioral design theory
  • Ph.D. and M.S. in Mechanical Engineering, California Institute of Technology; B.S. in Mechanical Engineering and Nuclear Engineering, University of California, Berkeley

 

Eric Huang
  • heuristic search, packing, constraint satisfaction, planning, scheduling
  • Ph.D., Computer Science, UCLA
  • former Micro Fellow and EGSA Angels Fellow

 

 

 

Matthew Klenk
  • qualitative reasoning, machine learning, planning, intelligent agents, spatial reasoning
  • worked in U.S. Naval Research Laboratory
  • Ph.D., Northwestern University EECS

 

Tolga Kurtoglu
  • 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

 

Linxia Liao
  • predictive and prescriptive analytics; system and components fault diagnostics and prognostics; signal processing; and machine learning algorithms
  • developing device fleet health management solutions for intelligent transportation systems
  • Ph.D., Industrial Engineering, University of Cincinnati; M.S. and B.S., Mechanical Science and Engineering, Huazhong University of Science and Technology (HUST) in China
  • one issued patent and seven pending patents

 

Julia Liu
  • 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

 

Rui Maranhão
Rui Maranhão
Applied Research Scientist

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  • research focuses on statistical and probabilistic techniques for testing and automatic fault localization of software intensive systems, as well as self-adapting to runtime failures. 
  • applying diagnostic and predictive techniques to other domains, such as healthcare and HVAC. 
  • P.h.D. Delft University of Technology, the Netherlands;  Software Technology Master Course, University of Utrecht, the Netherlands; Systems and Computer Science, University of Minho, Portugal

 

Raj Minhas
Raj Minhas
Vice President, Interaction and Analytics Lab

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  • directs wide range of research activities including high performance computing, cognitive science, agile organizations and machine learning
  • Ph.D. and M.S.. Electrical and Computer Engineering, University of Toronto; B.E., Delhi University

 

Marzieh Nabi-Abdolyousefi
  • control, optimization, networked dynamics systems, robotics, and flight dynamics, in energy, transportation, multi-agent system, and healthcare
  • Ph.D. in Aeronautics and Astronautics and M.Sc. in Mathematics from University of Washington

 

Bob Price
  • 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

 

Ajay Raghavan
  • 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 

 

Aaron Wilson
  • research lies within the field of machine learning where he has focused on automated decision making, active learning, inference, and reasoning
  • currently working on active learning, behavior analysis, and relational analysis to support anomaly detection
  • Ph.D., Computer Science, Oregon State University