James Johansen, PhD

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Assistant Professor, Department of Computer Science, Engineering, Mathematics, Physics, and Statistics

Email: jjohansen@apu.edu

Office Location: West Campus, Segerstrom 113

Dr. Johansen has extensive industry and academic experience working on a variety of interdisciplinary topics. He has broad industry expereince in systems engineering and academic teaching and research experience at several universities. He has an interdisciplinary PhD from Liberty University focusing on faith and science, and how faith makes us better able to do good science. He has a MS and BS in Electrical Engineering from USC and two MA degrees from Biola in Science and Religion and Christian Apologetics. He enjoys helping students master the material required to succeed in STEMM fields. He is committed to teach individuals as whole persons, seeking to help them develop character as well as skill development.

Education

  • PhD, Theology and Apologetics, with Biology and Systems Engineering, Liberty University
  • Machine Learning Graduate Courses, Stanford University
  • MA, Christian Apologetics, Biola University
  • MA, Science and Religion, Biola University
  • Graduate Certificate in Unix and C Programming, UCLA
  • MS, Electrical Engineering, USC
  • BS, Electrical Engineering, USC

Credentials/Certifications

  • NASA Headquarters Award – GPS Use in Space
  • Institute on Navigation (ION) Distinguished Service Award
  • Numerous Customer Accommodation Letters
  • Three Individual Performance Recognition Awards from the Aerospace Corporation
  • Individual Spot Performance Awards from the Aerospace Corporation
  • Individual Spot Performance Award from the MITRE Corporation
  • Customer Recognition Awards
  • Lockheed Martin NOVA Award
  • NSF, NASA, DHS, DARPA, and Other Organizations – Numerous examples of getting direct government funding
  • Boeing Master’s Fellowship for my master’s degree in electrical engineering

Academic Area

  • School of Humanities and Sciences

Expertise

  • Systems Engineering, including applying Systems Engineering towards biological systems
  • Computer Architecture and Design, Information Systems
  • CubeSats, Space Systems, and Remote Sensing
  • Model-based Systems Engineering (MBSE)
  • Neuromorphic Computing
  • Machine Learning
  • Deep Learning

Courses Taught

  • CS 160 – Discrete Structures
  • CS 260/ENGR 260 – Algorithms and Data Structures
  • CS 360/ENGR 360 – Computer Architectures and Organization
  • CS 470 – Software Engineering
  • CS 480 – Senior Capstone Project
  • ENGR 101 – Introduction to Engineering
  • ENGR 345 – Systems Engineering Principles
  • WRIT 242 – Technical Communication