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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
  • design of state-of-the-art control, planning, and optimization algorithms for real physical systems
  • interface between planning and control, control and coordination of large-scale distributed systems
  • manufacturing systems, energy systems
  • Ph.D. in Biophysics & M.S. in Electrical Engineering, U.C. Berkeley; A.B. in Physics, Harvard

 

Johan de Kleer
  • PARC Research Fellow and leads the Model-based Reasoning area
  • co-invented the field of Qualitative Reasoning;  invented the Assumption-based Truth Maintenance System (ATMS) and the field of model-based diagnosis
  • 19 patents; over 100 published papers and co-authored three books
  • Recipient of the "Lifetime Achievement Award" at the 25th International Workshop on Principles of Diagnosis and Computers and the "Computers and Thought Award" at the International Joint Conference on Artificial Intelligence
  • Ph.D., Artificial Intelligence EECS and S.M., Computer Science EECS, Massachusetts Institute of Technology; B.Sc. (Honors), Mathematics and Computer Science, University of British Columbia, Canada

 

Filip Dvorak
  • working on new planning approaches for energy control and mobility
  • 7 years of independent research experience in artificial intelligence planning, machine learning and big data
  • 13 conference publications and 1 journal
  • Ph.D., M.S., RNDr. and B.S. at Charles University, Prague

 

Alexander Feldman
  • model-based diagnosis, artificial intelligence, and cyber-physical systems
  • over 40 publications in leading conference proceedings and international journals
  • Ph.D. in Computer Science and M.Sc. in Parallel and Distributed Computer Systems, Delft University of Technology

 

Lina Fu
  • data mining, statistical modeling and spatial temporal analytics
  • Ph.D. and M.S. in Electrical and Computer Engineering, Ohio State University, B.S., Electrical Engineering, Zhejian University

 

Alvaro Gil
  • machine learning, control algorithms and optimization
  • Ph.D., Electrical Engineering, Ohio State University, M.S. and B.S., Electrical Engineering, Instituto Universitario Politecnico

 

Eric Gross
  • experimental design, systems modeling, optimization, and control
  • Ph.D. and M.S, Dynamic Systems and Controls, University of California Berkeley, B.S., Mechanical Engineering, Rensselaer Polytechnic Institute

 

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

 

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

 

Gregory Kott
  • research interests include cloud computing, online analytics, analytics as a service with 20 years experience in research, design and development of hardware and software products
  • Ph.D. and ME, Mechanical Engineering, Rensselaer Polytechnic Institute, BS, Mechanical Engineering, Rochester Institute of Technology

 

Tolga Kurtoglu
Tolga Kurtoglu
Vice President, Director of System Sciences Lab (SSL)

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  • Vice President, System Sciences Lab (SSL)
  • Directs research programs in artificial intelligence, machine learning, control, planning, optimization, and high performance analytics for cyber-physical systems
  • Leading business development, strategy, execution, and technology commercialization for a portfolio of product and service offerings
  • previously at NASA Ames Research Center and Dell Corporation
  • PhD, UT Austin, MS, Carnegie Mellon University, Mechanical Engineering

 

Lei Lin
  • exploring novel methods and models to analyze the wealth of transportation-related data for insights and applications to improve the urban mobility
  • Ph.D., Philosophy, University at Buffalo, M.S., Computer Science, University at Buffalo, M.S., Systems Engineering, Beijing Jiaotong University

 

Rui Maranhão
  • 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

 

Shiwali Mohan
  • adaptive agents for facilitating positive health behavior change and on knowledge representation and acquisition for task-driven dialog agents.
  • artificial intelligence, agent design and learning, cognitive systems and architectures, and psycholinguistics
  • Ph.D. from University of Michigan's Computer Science and Engineering department; M.S. in computer science from University of Michigan; a B.Tech in instrumentation and control engineering from Delhi University in India

 

Marzieh Nabi
  • 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
  • Manages the ACES area, focused on systems health and condition management technologies
  • Interests span sensing, modeling, diagnostics, and prognostics
  • PI on ARPA-E AMPED SENSOR project on fiber optic battery management systems
  • Ph.D., M.S., Aerospace Engineering, University of Michigan, Ann Arbor; B.S., Mechanical Engineering, IIT Bombay 

 

Ryan Rossi
  • machine learning, statistical relational learning, graph mining
  • high-performance analytics, relational machine learning, scalable learning and inference
  • Ph.D., Purdue University

 

Eric Saund
  • computational vision, specializing in perceptual organization in the domain of document images.
  • ScanScribe document image editor
  • B.S. in Engineering and Applied Science, California Institute of Technology. Ph.D. in Cognitive Science from the Massachusetts Institute of Technology

 

Marina Tharayil
  • business process modeling and optimization
  • Ph.D., University of Illinois, B.S., Mechanical Engineering, University of Illinois

 

Rong Zhou
  • manages High-performance Analytics area 
  • interests include artificial intelligence; high-performance analytics; machine learning; parallel model checking
  • holds 21 US patents; 14 international patents in the areas of parallel algorithms, planning and scheduling, disk-based search and diagnosis