I'm excited to announce that I will be starting a new course focused on the practical application of machine learning in engineering.
➡️ Click here to view the course syllabus and materials!
I am honored to have accepted a scholarship from the Politecnico di Torino's Department of Energy after our team's success in a prestigious international Galileo Ferraris' Contest.
| Competition | International "Galileo Ferraris' Contest" |
| Organizer | Politecnico di Torino |
| Achievement | 2nd Place (Novelty Category, Academic Teams) |
| Award | Scholarship for "assessing data-driven methodologies for the multi-physics simulation of traction electrical machines" |
I had the privilege of leading the IEML Team from Amirkabir University of Technology. Our team consisted of myself and my talented colleague.
- Tohid Sharifi (Team Lead)
- Ali Jamali-Fard
Our 2nd place finish was awarded for our work in developing a novel sequential machine-learning algorithm called SBRTO. This algorithm enhances surrogate models for electrical machine design, providing key innovations:
- Hybrid Integration: It combines a Bayesian regularization-enhanced multi-layer perceptron artificial neural network (MLPANN) with the teaching-learning-based optimization (TLBO) algorithm.
- Advanced Modeling: We successfully incorporated a population-based training approach, a new sequential training method, and multi-objective metaheuristic-based feature selection.
- Proven Results: Our method demonstrated significantly improved accuracy, efficiency, and generalization capabilities when tested on complex V-type permanent magnet synchronous motor datasets.