Soma Tohidinia

Programming Languages & Libraries: Python (advanced), SQL (intermediate), PyTorch, Keras, Scikit-learn, Transformers, NumPy, SciPy, Pandas, Matplotlib, Seaborn

Machine Learning & Data Science: Supervised & Unsupervised Learning (SVM, Decision Trees, k-Means, PCA), Semi-Supervised & Active Learning, Transfer & Online Learning, Feature Engineering, Anomaly Detection, Time Series Modeling (ARIMA, LSTM, Informer), Statistical Analysis (Bayesian, Hypothesis Testing), Survival Analysis, NumPy, SciPy, pandas

Deep Learning & Architectures: MLP, CNN, RNN, LSTM, GRU, Transformers (BERT, ViT), Autoencoders, GANs, Curriculum Learning, Knowledge Distillation, NAS

Computer Vision & Image Modeling: Image Classification, Object Detection (YOLO), Segmentation (U-Net), Generative Models (CycleGAN), Self-Supervised Vision (SimCLR, BYOL)

AI Ethics & Explainability: XAI (SHAP, LIME), Robustness to Adversarial Attacks, Fairness-Aware Modeling, Responsible AI Practices, Captum, Integrated Gradients, Feature Attribution Methods, post-hoc model interpretation, surrogate modeling, end-to-end explainability pipelines

Signal Processing & Neurodata: MNE-Python, EEG signal processing, spectral analysis (PSD), Common Spatial Patterns (CSP)

Python programming

Statistical analysis

SQL databases

Scikit-learn

Data mining

Neural networks

Natural language processing

Database management

Big data analytics

Data visualization