Ole Mengshoel
Location: (San Francisco Bay Area)
Personal Research Web Page: http://ti.arc.nasa.gov/people/omengshoel
Keywords: Bayesian networks; Inference; Machine Learning; Stochastic Local Search; Evolutionary Algorithms; Aerospace Vehicle Health Management; Electrical Power Systems; Real-Time Systems; Dependable Systems; Aerospace Vehicles; Software/Knowledge Engineering.
Posted on: Tuesday, June 2nd, 2009
Broad Research Area: AI / Machine Learning / Robotics / Vision, Information Assurance / Security / Privacy / Cryptography, Mobile / Ubiquitous / Embedded Computing, Software Engineering
Research Interests:
Dr. Ole J. Mengshoel is a Senior System Scientist with CMU Silicon Valley at the NASA Ames Research Center. His current research focuses on reasoning, diagnosis, decision support, reasoning, and machine learning under uncertainty – often using Bayesian networks – with aerospace applications of interest to NASA. Additional research interests include resource allocation and scheduling in real-time systems, intelligent user interfaces, information assurance, evolutionary algorithms, knowledge acquisition, and knowledge engineering. Dr. Mengshoel has managed and provided hands-on leadership in a wide range of research and development projects. He has successfully developed technical results and software that have or are being matured and transitioned into the aerospace, defense, finance, education, electronic commerce, and manufacturing sectors. Dr. Mengshoel has published over 35 articles and papers in journals and conferences, and holds 4 U.S. patents. He holds a Ph.D. in Computer Science from the University of Illinois, Urbana-Champaign. His undergraduate degree is in Computer Science from the Norwegian Institute of Technology, Norway (now NTNU). Prior to his work with NASA, he was a research scientist in the Knowledge-Based Systems at SINTEF (Scandinavia’s largest independent research organization) and in Decision Sciences Group at Rockwell Scientific.
Contact Information:
Email: email obfuscated - click to reveal
Phone: 650-604-4199
