• Cognitive robotics, learning from demonstration
• Machine learning and artificial intelligence
• Vision-based control of robots
• Control systems and automation

Alex Vakanski is an assistant professor in Industrial Technology. At the University of Idaho in Idaho Falls, he teaches courses in the areas of manufacturing, robotics, CAD design and quality control. His research efforts are focused on enhancing cognitive abilities of robots and machines, through the development of algorithms for visual perception and comprehension of the world.

• Mathematical Modeling of Human Motions using Recurrent Neural Networks, MAG – IMCI
• Development and Commercialization of a Visual Learning System for Robot Programming by Demonstration, I2I-NSERC

• A. Vakanski, and F. Janabi-Sharifi, Robot Learning by Visual Observation, John Wiley & Sons, ISBN-10: 1119091802, ISBN-13: 978-1119091806, 2017.
• A. Vakanski, J. M. Ferguson, and S. Lee, "Mathematical modeling and evaluation of human motions in physical therapy using mixture density neural networks," Journal of Physiotherapy and Physical Rehabilitation, vol. 1, no. 4, pp. 1–10, 2016.
• A. Vakanski, I. Mantegh, A. Irish, and F. Janabi-Sharifi, "Trajectory learning for robot programming by demonstration using Hidden Markov Model and Dynamic Time Warping," IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics, vol. 42, no. 4, pp. 1039 - 1052, 2012.
• E. Nematollahi, A. Vakanski, and F. Janabi-Sharifi, "A second-order conic optimization-based method for visual servoing," Journal of Mechatronics, vol. 22, no. 4, pp. 444 - 467, 2012.

• ASNT Faculty Grant Award, awarded by the American Society for Nondestructive Testing, 2015