Dr. Chris Venour |
Chris Venour
has a PhD in Computer Science from Principal Data Scientist
Chris is a Data Scientist and Machine Learning researcher · Controlling the flight of drones via Deep Learning and microcontrollers. · Automatically extracting semantic information from text using Deep Learning. · Anomaly detection in the Maritime environment. This work was performed for Defence Research and Development Canada (DRDC) Valcartier. The system automatically retrieves and collates shipping data, creates an OWL ontology from this information, uses a Reasoner to automatically search for anomalies in the ontology, and displays these anomalies in a Google Earth visualization of the Maritime domain. Expertise · Machine Learning and Artificial Intelligence: Deep Learning, Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Decision Trees (xgboost), Tensorflow, Keras, BERT, Principal Components Analysis, Natural Language Processing. · Internet of Things: AVR programming (i.e. programming microcontrollers such as the ATmega328P), Raspberry PI, Arduino. · Visualization programming: Unity 3D (game engine), Google Earth API, D3.js · Technical Writing: With degrees in English and Computer Science, Chris is also a respected technical writer. He has worked as a technical writer for Salience, Testfire Labs, the University of Aberdeen, the University of Calgary, Shell Canada, and Canadian Pacific Railways. Qualifications · PhD, Computer Science, University of Aberdeen, 2013. · M.Sc., Computer Science, Queens University, 1999. · MA, English, University of Victoria, 1992. · BA (Honours) English, University of Calgary, 1990. Contact Chris Venour for a full curriculum vitae. |
Chris Venour PhD, MSc, MA |