Academic Experiences

Thesis: Architecting a Deep Learning-Based Digital Twin and Reinforcement Learning Control Pipeline for Wind Turbines.

🔗 View the Repository: github.com/itreza7/master-thesis

I designed and deployed an end-to-end, data-driven optimization framework for cyber-physical systems, graduating Rank 1 in my cohort. The core objective was to maintain a stable 5MW power output under highly stochastic environmental conditions without relying on computationally expensive physics simulations. To achieve this, I first developed a temporal forecasting module utilizing a BiLSTM network with a 2-hour sliding window to predict upcoming wind dynamics, validating its accuracy with rigorous RMSE and $R^2$ metrics.

To solve the computational bottlenecks of agent training, I constructed a dynamic surrogate environment—a localized Digital Twin. I used K-means++ clustering to divide the operational data into distinct regimes, training specialized Multi-Layer Perceptrons (MLPs) for each cluster to accurately simulate the physical turbine's power generation. Finally, I trained a Rainbow DQN reinforcement learning agent. To ensure the physical safety of the turbine's mechanical actuators, the agent utilized a continuous-to-discrete incremental action space ($\Delta \theta$) and a squared-error reward function to optimize blade pitch. The entire architecture was built with rigorous, industry-standard software engineering practices, bridging theoretical control methodologies with scalable, deployment-ready code.

In my role as a Multimedia Teaching Assistant, I mentored students in applying Deep Learning and Computer Vision principles using the Python ecosystem. I provided technical guidance on architecting CNNs and DNNs with PyTorch, while integrating OpenCV for image processing and TorchAudio for signal analysis. Additionally, I facilitated the use of Scikit-Learn for traditional machine learning workflows and Gradio to build interactive interfaces for complex neural network models.

As a Laboratory Instructor at Amirkabir University of Technology, I led the Logic Circuit Laboratory, focusing on the practical application of hardware description and digital design. I provided technical instruction in VHDL and the programming of FPGA boards, guiding students through the design, simulation, and physical implementation of complex logic systems.

As a Teaching Assistant for Digital Systems I at the University of Guilan, I supported Dr. Shahbaz Reyhani in delivering core curriculum to undergraduate students. I facilitated learning through weekly tutorial sessions and the development of custom educational slides and problem sets. Beyond instruction, I provided technical mentorship for final projects using Proteus simulation software and managed the end-to-end grading process for assignments and exams.