Dan Mcreynolds, P.Eng., Ph.D. Email & Phone Number

My passion is for the discovery, understanding, and application of the constraints that make vision possible in humans and machines.The domain for my work is in computational vision, which makes explicit the context for realizing the models that embody the constraints, as mathematical, from which are derived representational and algorithmic expressions suitable for implementation on a computer. I am a specialist in the research, design and implementation of computer vision algorithms.As a graduate of the Laboratory for Computational Intelligence in the Computer Science Department of the University of British Columbia I am the co-author of several papers on topics such as model based recognition, structure-from-motion, feature detection and matching, and image registration. Following my training in the LCI my approach is grounded in the information processing theory of the brain best promulgated by David Marr.I perform the research and implement the algorithms for systems that, for example, do target acquisition and tracking, human face detection, object recognition, image stabilization, and simultaneous localization and mapping. The application domains include systems that process unmanned aerial vehicle acquired imagery, optical sensor-based systems for human computer interaction, and optical target tracking for military applications and sports.Recently, I have researched and implemented machine learning algorithms for hand writing detection in cluttered backgrounds, prediction and classification for business use cases and financial products using Keras with Theano and TensorFlow backends, and with Microsoft Azure Machine Learning Studio.I am also the co-inventor of several granted patents and pending patents in the area of human computer interaction with optically based systems.

Listed skills include Algorithms, Computer Science, Software Engineering, Object Oriented Design, and 10 others.

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  The University Of British Columbia / Ubc

  Computer Science