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Kyle Arakaki
Kyle Arakaki
Member of Technical Staff

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Fangzhou Cheng
  • Data-driven solutions for system prognostics and health monitoring
  • Condition monitoring, fault diagnostics and fault prognostics
  • Ph. D., Electrical Engineering, University of Nebraska-Lincoln; B. Eng., Electrical Engineering, Zhejiang University, China


Kyle Dent
  • novel human-computer interaction technologies
  • author of Postfix: The Definitive Guide (O'Reilly & Associates, 2003)
  • M.S., Computer Science, Columbia School of Engineering and Applied Science


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


Gaurang Gavai
  • applications in embedded reasoning and machine learning with a focus on social network data analysis and technical infrastructure development therein
  • Master's in Computer Science with a specialization in Machine Learning, Georgia Institute of Technology; Bachelor's in Information Technology, University of Mumbai


  • machine learning algorithms
  • self-aware and self-healing cyber physical systems
  • Ph.D., Electrical and Computer Engineering, Yale University; M.S., Electrical and Computer Engineering, University of Michigan, Ann Arbor; B.S., Radio Communication Engineering, Yonsei University, Seoul, South Korea


Raj Minhas
Raj Minhas
Vice President, Director of 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


Lottie Price
  • automating monitoring of printer repair reports 
  • deep learning techniques 
  • M.Sc., Computer Science, University of Saskatchewan


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 


Kalai Ramea
  • data scientist, machine learning engineer, quantitative modeler
  • expertise in big data analytics, applied machine learning and deep learning, statistical and numerical modeling, operations research
  • Ph.D., University of California, Davis; M.S., University of Southern California; B.E., Anna University, India


Palghat Ramesh
  • machine learning, computer vision, modeling and simulation
  • Ph.D., Cornell University; M.S., Computer Science and Data Analytics, University of Rochester; B.S., Mechanical Engineering, Indian Institute of Technology
  • 53 patents, 50 publications


Matthew Shreve
  • behavior recognition and surveillance, computer vision, image processing and artificial intelligence
  • Ph.D., Computer Science, University of South Florida, M.S., Mathematics, Youngstown State University


Hong Yu
  • designing simulation tools that incorporate fault diagnosis into systems modeling
  • model-based diagnosis for complex electromechanical systems
  • Ph.D. in Mechanical Engineering from the University of Delaware; Bachelor in Mechanical Engineering from Huazhong University of Science and Technology (HUST) in China


Maksym Zhenirovskyy
  • software development, numerical methods, machine-learning algorithms, graph theory and complex networks, data analysis
  • working on expanding the library of SysX components.  The SysX project is developing a platform which embodies the diagnostics tools and knowledge PARC has developed over recent years.
  • Ph.D., Physics, Institute of Physics of the NAS of Ukraine; M.Sc., Electrical Engineering, National Technical University of Ukraine “KPI”