Dr. James A. Crowder currently serves as a Systems Fellow for Colorado Engineering Inc. and Subject Matter Expert (SME) in Autonomous Systems, Artificial Intelligence, and Systems Architecture. He holds a BS in Electrical Engineering, an MS in Electrical Engineering in Signal Processing, an MS in Applied Mathematics, and a PhD in Electrical Engineering and Applied Mathematics. Dr. Crowder has several patents pending in Artificial Intelligence and has over 100 published, peer-reviewed papers. Recent book publishing efforts with Springer Scientific books include: "Artificial Cognition Architectures," "Systems Engineering, Agile Design Methodologies," and "Agile Project Management: Managing for Success," as well as chapters in several books on Big Data, Biomedical Engineering, and Cyber Physical Systems. His professional efforts include serving as a technical advisor and mentor to a STEM school in Douglas Country, Colorado, the Alexandria School of Innovation, as well as a technical reviewer for the Journal of Supercomputing and the Journal of Systemics, Cybernetics, and Informatics. Dr. Crowder has been interviewed, and articles written about his work in Artificial Intelligence, by Popular Science, Defense One, the Washington Post, Discovery News, and has written an article for TechCrunch that was published in June, 2016.

Dr. John N. Carbone, an Engineering Fellow, has served Raytheon Company and the defense industry for ~28 years. Dr. Carbone holds a BS in Computer Science, an MS in Engineering, MS equivalent in Software and Systems Engineering, and a PhD in Mechanical Engineering. Dr. Carbone has several national and international software patents and many peer-reviewed publications. Recent book publishing efforts for Springer Scientific books include topics on Applied Cyber Physical Systems, Biomedical Engineering, Artificial Cognition Architectures and Multi-Disciplinary Systems Engineering. Dr. Carbone's professional efforts include Computer Science board membership and curriculum advisor at Baylor University, Texas Tech University, and Texas A&M Commerce, as well as board membership for the indexed Journal of Integrated Design and Process Science (JIDPS), passionate STEM Facilitator, ACM Member and long-standing member of the Society of Design and Process Science (SDPS).

Dr. Shelli Friess is a Licensed Professional Counselor in Colorado, a National Certified Counselor, and an Approved Clinical Supervisor. Most of her experience in counseling has been with survivors of trauma, including domestic violence and sexual assault. She has over 18 years of experience as a counselor, clinical supervisor, and program director. She has also worked with offenders of domestic violence on parenting skills. In addition, she worked with children in elementary and middle school and has experience working with children in residential treatment. Dr. Friess is a core faculty at Walden University in the School of Counseling, within the College of Social and Behavioral Sciences. Her history includes earning her BA from University of Colorado with a major in psychology. She earned her MA from the University of Northern Colorado in community counseling with an emphasis in marriage and family systems. In addition, she earned her Ed.D. from Argosy University in counselor education and supervision. Dr. Friess has published several peer reviewed papers on Artificial Intelligence. Recent book publishing efforts with Springer Scientific books include: "Artificial Cognition Architectures," "Systems Engineering, Agile Design Methodologies," and "Agile Project Management: Managing for Success."

Explores the concepts of Artificial Psychology and Artificial Neuroscience as applied to advanced artificially cognitive systems

Provides insight into the world of cognitive architectures and biologically-based computing designs which will mimic human brain functionality in artificial intelligent systems of the future

Provides description and design of artificial psychological modeling to provide insight into how advanced artificial intelligent systems are learning and evolving

Explores artificial reasoning and inference architectures and the types of modeling and testing that will be required to "trust" an autonomous artificial intelligent systems