Ahmed Shokry awarded for his work on machine-learning
Ahmed Shokry’s research areas include machine learning and artificial intelligence applications for industrial processes operation, prognostics and health management, and precision agriculture. The Excellence Award in Computer Aided Process Engineering (CAPE) acknowledges his outstanding PhD thesis completed under the supervision of Professor Antonio Espuña at the Polytechnic University of Catalonia, Barcelona, Spain. This work focused on the improvement of existing decision-making methods and procedures in the chemical industry. Ahmed Shokry developed machine learning models and solution methodologies able to consistently consider the different circumstances this decision-making should address, with different objectives and constraints, working together with other CAPE tools.
This work has been awarded for its potential impact in the scientific and industrial community. Moreover, the examples and case studies come from different fields such as reaction engineering, biochemistry, energy and environmental engineering. The originality of the work not only stems from the highly innovative way in which classical artificial intelligence, machine learning and optimization techniques are used and combined to develop novel but also from the wide range of process operation modules covered and from the completely different process behaviours that these methods were able to approximate and capture: continuous, discrete, static, dynamic and, most importantly, optimal behaviour (i.e., optimal with respect to uncertain parameter changes).
The award has been presented to the two winners at the 32th European Symposium on Computer Aided Process Engineering held in Toulouse.
About Ahmed Shokry
Ahmed Shokry obtained his bachelor degree in Industrial and Production Engineering and Master in Mechanical Design and Production Engineering from Zagazig University, Egypt, and his Diploma of advanced studies and PhD in Chemical Process Engineering from the Technical University of Catalonia, Spain. Currently, he holds the position of Research Engineer at the Center for Applied Mathematics (CMAP*)
Currently, Ahmed is participating the Chair of "AI and Positive Maintenance" to develop new machine learning-based methods to detect early signs of degradation in rechargeable batteries and other components of locomotives to enable predictive maintenance. He is also working in the Data Science for Process Industry chair to improve control and monitoring of complex industrial processes. Both chairs are led by Eric Moulines, professor at Ecole Polytechnique.
*CMAP: a joint research unit CNRS, École Polytechnique - Institut Polytechnique de Paris