M.Sc. in Artificial Intelligence
Azad University, Tehran North Branch 2023 — Graduated 2025- Master's Thesis: "Developing Transformer-based Deep Learning models for Signal Decoding in Brain-Computer Interface"
- Thesis Grade: 20 / 20 (Perfect Score)
- Rank: Top student in the AI department
- Core Focus & Expertise:
- Neuro-AI & BCI: Robust Motor Imagery decoding and Signal Denoising.
- Architectures: Convolutional Transformers (CvT), Hybrid Transformer-RNNs, and ViTs.
- Explainable AI (XAI): Model Interpretability (Grad-CAM, SHAP) and Artifact-Dependency analysis (RSA).
- Optimization: Automated Machine Learning via Hyperparameter Optimization (Optuna).
B.Sc. in Computer Engineering
Roshdiyeh Higher Education Institute 2017 — 2021- Orientation: Software Engineering.
- Developed a strong foundation in Programming (C++, Java, Python), Algorithms, Data Structures, and Software Architecture.
- Completed various projects in software development and database management.
--- ### 📜 Relevant Coursework & Academic Expertise * **Advanced Deep Learning:** Architecture design using **PyTorch**, focusing on **Convolutional Transformers (CvT)**, **Vision Transformers (ViT)**, and Hybrid Transformer-RNN models. * **Digital Signal Processing (DSP):** Neural signal analysis, advanced **EEG filtering**, artifact removal techniques (**ICA, ASR**), and feature extraction using **MNE-Python** and **EEGLAB**. * **Digital Image Processing:** Implementation of **U-Net** architectures for medical image segmentation and spatial enhancement algorithms. * **Machine Learning:** Statistical pattern recognition, model evaluation, and automated hyperparameter optimization using **Optuna**. * **Computational Neuroscience:** Exploring the synergy between biological neural principles and artificial intelligence architectures.
