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PEOPLE:

 

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

 

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

 

Warren Jackson
  • large-area printed electronics; metal oxide electronics; many-sensor actuator control systems; task-based system design
  • machine learning; sensor/actuator machine learning; biosensing
  • Ph.D., M.S., Physics, UC Berkeley; Fellow, APS; 100 patents; 250 publications

 

Deokwoo
  • 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

 

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 

 

Parham Shahidi
Parham Shahidi
Research Scientist

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  • research focus on artificial intelligence for cyber-physical systems and predictive analytics systems for safety-sensitive applications
  • active contributor to professional organizations including ASME, VDI, JVC and the PHM Society; received the 2015 Best Technical Paper Applied award of the Prognostics and Health Management Society
  • Ph.D., Mechanical Engineering, Virginia Tech; B.S., Mechanical & Process Engineering, TU Darmstadt, Germany

 

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