Skip to main content

About Ole J Mengshoel

Dr. Ole Jakob Mengshoel is a professor in Artificial Intelligence at the Department of Computer Science (IDI) at the Norwegian University of Science and Technology (NTNU) in Trondheim, Norway. He is the head of the Norwegian Open AI Lab. He is an adjunct faculty at the Carnegie Mellon University (CMU), in the Electrical and Computer Engineering (ECE) Department. Prior to his work with NTNU, he was a Principal Systems Scientist with CMU Silicon Valley at the NASA Research Park; a Senior Research Scientist with USRA/RIACS in the Intelligent Systems Division at the NASA Ames Research Center; a Research Scientist in the Decision Sciences Group at Rockwell Scientific (now Teledyne Scientific and Imaging); and a Research Scientist in Knowledge-Based Systems at SINTEF (Scandinavia's largest independent research organization).

His research focuses and has focused on reasoning, diagnosis, decision support, and machine learning under uncertainty - often using Bayesian networks – with applications. 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. Working with companies such as Boeing, Rockwell Automation, and Rockwell Collins, he has successfully developed new technologies 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 100 articles and papers in journals and conferences, and holds 4 U.S. patents. He has 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).

Twitter: @OleMengshoel


Present Principal Systems Scientist, Carnegie Mellon University

Curriculum Vitae

Enter a valid date range.

Enter a valid date range.

Big Data (6)

Cyber-Physical Systems (2)

Deep Learning (3)

Earth Science (1)

Genetic Algorithms (2)

Human Activity Recognition (5)

Probabilistic Graphical Models (2)

Recommender Systems (5)