Research & Laboratory Experience
- Comprehensive statistical analysis of HLA allele frequencies in Azeri and Kurd populations using 6 years of clinical datasets (N > 5,000).
- Applied chi-square tests, Fisher's exact tests, Hardy–Weinberg equilibrium, and linkage disequilibrium mapping.
- Built reproducible R and Python pipelines for automated data cleaning, structural quality control, and population genetics evaluation.
- Developed novel fuzzy logic-based models for input current conversion in LIF neuron models, enhancing baseline biological realism by 35% over traditional static systems.
- Executed simulations in Python/MATLAB; validated variants against empirical neuronal spike trains.
- Stroke Prediction: Built ML architectures (Random Forest, XGBoost, MLPs) hitting an 87% predictive accuracy and 0.91 AUC-ROC.
- Lung Cancer Classification: Built Deep Learning pipelines (U-Net, ResNet) for CT nodule segmentation yielding 92% sensitivity and 88% specificity.
- Thyroid Cancer Radiomics: Handled extraction matrices for 400+ ultrasound features utilizing downstream feature selection algorithms for diagnostic optimization.
Education
Thesis: "An Investigation into Fuzzy Modeling Techniques for Input Current Conversion in LIF Neuron Models" — Supervisor: Dr. Fariba Bahrami.
Coursework: Advanced Calculus, Linear Algebra, Mathematical Statistics, Differential Equations, Probability, Numerical Analysis, Fuzzy Mathematics, Data Structures, Stochastic Processes, Advanced Bioinformatics.