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.
In Proceedings
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![[DOI]](https://cerc-datascience.polymtl.ca/wp-content/plugins/papercite/img/external.png)
Neal, C., Al Mallah, R., Fernandez, J. & Lodi, A. (2020) Analyzing the Resiliency of Microgrid Control Algorithms Against Malicious Input , 1-6.
[Bibtex]@INPROCEEDINGS{9255704, author={C. {Neal} and R. {Al Mallah} and J. {Fernandez} and A. {Lodi}}, booktitle={2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)}, title={Analyzing the Resiliency of Microgrid Control Algorithms Against Malicious Input}, year={2020}, volume={}, number={}, pages={1-6}, doi={10.1109/CCECE47787.2020.9255704}}