Expertise - Data Sciences
The NPS Data Science & Analytics Group Team
Masters of Information Technology Management, Naval Postgraduate School, 2011
Research Interests: Virtualization Technologies and Cloud Computing, Wireless Networking and Thin and Zero Client Devices, Alternative Power and Efficient Computing, My current thesis work is on Floating Points Per Second (FLOPS) over Kilowatt Hour (kWh) in past and current Virtual Systems, starting with the IBM System 370 and examining presumed gains in efficiency of our modern virtualized systems compared to the earlier main frame model.
Ph.D., Standard University
Bio: Neil Rowe, Ph.D., is Professor of Computer Science at the Naval Postgraduate School where he has been since 1983. He has a Ph.D. in Computer Science from Stanford University. His main research interests are artificial intelligence, processing of big data, the modeling of deception, information security, and digital forensics. He is the author of a book on artificial intelligence, a book on cyberdeception, and 220 refereed technical papers.
Ph.D., Cornell University, 1986
Teaching Interests: Simulation analysis and statistics
Research Interests: Design of experiments, data-intensive statistics, and robust selection, with applications to simulation experiments, military operations, manufacturing, and health care.
Ph.D., Naval Postgraduate School, 2005
Teaching interests: Digital Signal Processing, Image Processing, Multisensor Data Fusion
Research interests: Remote Sensing, Multirate Signal Processing, Multisensor Data Fusion, Remote Sensing
Ph.D., Naval Postgraduate School, 2008
Teaching Interests: Adversarial Cyber Operations, Fundamentals of Computer Security, Algorithms, Introductory Programming.
Research Interests: Cyber operations and systems; data science and cloud computing; security modeling of systems & high assurance system verification.
Ph.D., Massachusetts Institute of Technology, 1992
Research interests: Big Data ML and AI for Combat, Deep Analytics, Reinforcement learning for Modeling Large-Scale Cognitive Reasoning, Big Data Architecture and Analytics, SOAR Architecture to Model Cognitive Functions in a Kill Chain, and Lexical Link Analysis (LLA).