Chris Neal
Polytechnique Montreal
Local AA-5505
Chris’ research is a joint collaboration with the Hydro-Quebec Research Institute (IREQ). It will focus on the the generation, processing, visualization of huge data in offline as well as real-time simulations for advanced measuring. This will involve using machine learning techniques to optimize a huge set of parameters, to detect system anomalies, and to manage global control strategies. Research Interests : Operations research on big data, machine learning, semantic web technologies, genetic algorithm, data visualization techniques, linked data, and cloud technologies.


Working papers

A. M. Aboussalah, C. Neal, 2016. Forecasting local warming: Missing data generation and future temperature prediction. G-2016-76