Bio

Chris King

Research Interests

Computer Vision, Robotics, Artificial Intelligence, Neural Networks, Genetic Algorithms

Experience

Research Assistant / University Of Nevada – Reno,NV

Led projects developing robots that autonomously navigate through their environment and interact with humans in real time:

Designed multiple systems from the bottom-up including: a real-time visual tracking system; an object identification module; a control algorithms for obstacle avoidance; an algorithm that allowed robots to autonomously pursue humans; a GUI for issuing requests to robots; software to display the results using charts, graphs, and videos.
Constructed a neural network evolved using a genetic algorithm that allowed simulated robots to autonomously learn basic control and obstacle avoidance, as well as search, pursuit, and evasion behaviors.
Contributed to and authored related publications.

Group Home Facilitator / Manager / Handyman / The Tungland Corporation – Flagstaff, AZ

Provided care, transportation, and support to developmentally disabled adults in a group home setting:

Managed staff, coordinated appointments, maintained daily records, and submitted reports.
Assisted in home and vehicle maintenance and repair.
Ensured residents were intellectually stimulated, physically active, and well taken care of.

Intern / Intel – Phoenix, AZ

Developed a storage-device controller emulator used for testing and debugging storage-device drivers:

Authored project documents including: Requirements, High Level Design, Test Plans, and Low Level Design.
Used C++ to code a Windows-based prototype of the emulator.
Helped port the emulation code to a Linux-based development board.
Scripted test cases using Perl and helped debug the emulation.

Undergraduate Teaching Assistant / Arizona State University – Tempe, AZ

Assisted in a course on "Microprocessor System Design":

Graded weekly homework assignments for 40-65 students.
Assisted students in assembly programming, hardware design, and understanding general concepts.
Tested and assisted in the debugging of weekly student programming exercises.

Research Assistant / Florida Atlantic University – Boca Raton, FL

Used EEG and FMRI to conduct experiments that investigated neural pathways involved in the processing of visual information:

Installed, modified, and maintained EEG laboratory equipment.
Coded stimulus presentation software.
Wrote programs in C and Mat-Lab to filter, edit, process, and display EEG data.

Research Assistant / Northern Arizona University – Flagstaff, AZ

Coded stimulus presentation programs for a visual perception laboratory.

Education

Doctor of Philosophy, Computer Science and Engineering
University of Nevada – Reno, NV
Advisor: Mircea Nicolescu & Monica Nicolescu
Dissertation: Efficient Object Detection and Tracking Using a Novel MSER-Based Approach

GPA: 3.85/4

Master of Science, Computer Science and Engineering
University of Nevada – Reno, NV
Advisor: Mircea Nicolescu & Monica Nicolescu
Thesis: Vision and Laser-Based Perception for Real-Time Autonomous Robotic Applications

GPA: 3.82/4

Bachelor of Science, Computer Science and Engineering

Arizona State University – Phoenix, AZ

Advisor: David Pheanis

GPA: 3.51/4

Bachelor of Science, Psychology with an emphasis in Biology

Northern Arizona University – Flagstaff, AZ

Advisor: Kathy Eastwood

GPA: 3.34/4

Funding Sources

National Science Foundation Award IIS-0546876
Office of Naval Research Award N00014-06-1-0611
Consortium for Embedded and Inter-Networking Technologies Scholarship

Website

http://number3114.wix.com/projects

Publications

Espina, M., Grech, R., Jager, D., Remagnino, P., Iocchi, L., Marchetti, L., Nardi, D., Monekesso, D., Nicolescu, M., King, C. (2011). Multi-Robot Teams for Environmental Monitoring. Innovations in Defence Support Systems – Intelligent Paradigms in Security, Springer-Verlag, 183-209.

Kelley, R., King, C., Ambardekar, A., Nicolescu, M., Nicolescu, M., & Tavakkoli, A.(2010). Integrating Context into Intent Recognition Systems. Proceedings of the International Conference on Informatics in Control, Automation and Robotics, (pp. 315-320). Funchal, Madeira, Portugal.

Kelley, R., King, C., Tavakkoli, A., Nicolescu, M., Nicolescu, M., & Bebis, G. (2008). An Architecture for Understanding Intent Using a Novel Hidden Markov Formulation. International Journal of Humanoid Robotics - Special Issue on Cognitive Humanoid Robots, 5(2), 203-224.

Kelley, R., Tavakkoli, A., King, C., Ambardekar, A., Nicolescu, M., & Nicolescu, M.(2012). Context-Based Bayesian Intent Recognition. IEEE Transactions on Autonomous Mental Development - Special Issue on Biologically-Inspired Human-Robot Interactions, 4(3), 215-225.

Kelley, R., Tavakkoli, A., King, C., Ambardekar, A., Wigand, L., Nicolescu, M., et al. (2013). Intent Recognition for Human-Robot Interaction. Plan, Activity, and Intent Recognition, Elsevier.

Kelley, R., Tavakkoli, A., King, C., Nicolescu, M., & Nicolescu, M. (2010). Understanding Activities and Intentions for Human-Robot Interaction. Human-Robot Interaction, 288-305.

Kelley, R., Tavakkoli, A., King, C., Nicolescu, M., Nicolescu, M., & Bebis, G. (2008). Understanding Human Intentions via Hidden Markov Models in Autonomous Mobile Robots. Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction, (pp. 367-374). Amsterdam, Netherlands.

King, C., Palathingal, X., Nicolescu, M., & Nicolescu, M. ( 2007). A Vision-Based Architecture for Long-Term Human-Robot Interaction. Proceedings of the International Conference on Human-Computer Interaction, (pp. 1-6). Chamonix, France.

King, C., Palathingal, X., Nicolescu, M., & Nicolescu, M. (2007). A Control Architecture for Long-Term Autonomy of Robotic Assistants. Proceedings of the International Symposium on Visual Computing, (pp. 375-384). Lake Tahoe, Nevada.

King, C., Palathingal, X., Nicolescu, M., & Nicolescu, M. (2009). A Flexible Control Architecture for Extended Autonomy of Robotic Assistants. Journal of Physical Agents, 3(2), 59-69.

King, C., Valera, M., Grech, R., Mullen, R., Remagnino, P., Iocchi, L., et al. (2012). Multi-Robot and Multi-Camera Patrolling. Handbook on Soft Computing for Video Surveillance, 255–286.

Tavakkoli, A., Kelley, R., King, C., Nicolescu, M., Nicolescu, M., & Bebis, G. (2007). A Vision-Based Architecture for Intent Recognition. Proceedings of the International Symposium on Visual Computing, (pp. 173-182). Lake Tahoe, Nevada.

Tavakkoli, A., Kelley, R., King, C., Nicolescu, M., Nicolescu, M., & Bebis, G. (2008). A Visual Tracking Framework for Intent Recognition in Videos. Proceedings of the International Symposium on Visual Computing, (pp. 450-459). Las Vegas, Nevada.