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Matthew Rutherford

Matt J. Rutherford

Associate Professor, Computer Science

matthew.rutherford@du.edu

303-871-3309 (Office)

http://mjrutherford.org

Personal

Engineering & Computer Science, 2155 E. Wesley Ave. Denver, CO 80208

What I do

I am a professor in the Department of Computer Science with a joint-appointment in the Department of Electrical and Computer Engineering. I am also the Deputy Director of the Unmanned Systems Research Institute and a faculty fellow of Project X-ITE.

Specialization(s)

Autonomous Systems, Embedded Systems, Software Engineering

Professional Biography

I am an Associate Professor in the Department of Computer Science at the University of Denver, an experienced software architect, designer and developer, and an entrepreneur. I'm interested in computer science topics at the intersection of software engineering and embedded and distributed systems.

Degree(s)

  • Ph.D., Computer Science, University of Colorado at Boulder, 2006
  • MS, Computer Science, University of Colorado at Boulder, 2001
  • BS, Civil Engineering, Princeton University, 1996

Professional Affiliations

  • Association for Computing Machinery
  • IEEE Computer Society

Research

Dr. Rutherford's research activities revolve around aspects of software system engineering and security for mobile, embedded, distributed, and parallel systems. He has published in the areas of unmanned / autonomous systems, software testing, cyber-physical systems, distributed stream processing, software engineering, distributed systems, content-based networking, model-driven development, generative programming and software configuration management. Dr. Rutherford's research projects are informed and applied to many of the collaborative, cross-disciplinary groups he is associated with. Currently, Dr. Rutherford is the Associate Director of (DU2SL) the DU Unmanned Systems Laboratory.

Key Projects

  • Modeling and Control of a NextGEn Circulation Control based UAV
  • CPS:TTP Option: Synergy: Dependable Multi Robot Cooperative Tasking in uncertain and dynamic environments
  • MRI Collaborative: Intergrated, Intelligent, Autonomous Unmanned Mobile Sensor

Featured Publications

Benini, A., Rutherford, M. J., & Valavanis, K. P. (2016). Real-time, GPU-based pose estimation of a UAV for autonomous takeoff and landing. Proceedings of the 2016 IEEE International Conference on Robotics and Automation (ICRA). IEEE.
Michanan, J., Dewri, R., & Rutherford, M. J. (2017). GreenC5: An Adaptive, Energy-Aware Collection for Green Software Development, 13, 42-60.