He is a dedicated researcher in Artificial Intelligence, with a strong focus on applying Machine Learning and Deep Learning techniques to healthcare, customer analytics, and decision-support systems. His work emphasizes the development of explainable AI models, causal inference, and advanced algorithms for disease diagnosis, medical decision-making, and predictive analytics.
Currently, he is pursuing a Master’s degree in Industrial Engineering at Sharif University of Technology, widely regarded as the top engineering school in Iran, with a GPA of 18.32/20 (4.0/4.0). Prior to this, he earned his Bachelor’s degree in Industrial Engineering at Iran University of Science and Technology, which was ranked as the best university in Iran by the QS rankings at the time of his enrollment, especially excelling in Industrial Engineering. His education at these leading institutions has equipped him with a strong foundation in data science, operations research, and optimization.
His research focuses on leveraging machine learning and large language models (LLMs) to solve challenges in healthcare and business analytics. He has co-authored several peer-reviewed papers, including "Enhancing Title and Abstract Screening for Systematic Reviews with GPT-3.5 Turbo," published in BMJ Evidence-Based Medicine, and "Assessing the Diagnostic Accuracy of Machine Learning Algorithms for Identification of Asthma in United States Adults based on NHANES Dataset," which is under revision for Scientific Reports. His work also includes developing advanced chunking strategies in retrieval-augmented generation models, with a paper prepared for submission to Artificial Intelligence in Medicine.
You can explore his publications and research profile on Google Scholar.
Currently, he is researching seizure prediction models using cardiac data (ECG) to improve early detection of epilepsy through AI, exploring the novel application of ECG data instead of the more commonly used EEG data for this purpose. His Master’s thesis explores causal relationships among key factors affecting customer retention using artificial neural networks, reflecting his broader interest in causal inference and explainable AI.
I have experience working with a wide range of programming languages, frameworks, and tools, including:
| Category | Tools |
|---|---|
| Programming Languages | Python · R · Bash |
| Tools and Platforms | Linux · Git · SQL · Ms Access |
| Machine Learning and Data Science | TensorFlow · Keras · Scikit-Learn · SciPy · NumPy · Pandas · Statsmodels · pm4py |
| Web Scraping and Data Processing | BeautifulSoup · Regex · OpenCV |
| Data Visualization | Matplotlib · Seaborn · Plotly |
| Simulation and Process Modeling | Arena Simulation Software · Camunda Modeler · Bizagi Studio · Disco |
| Business Intelligence and Reporting | Power BI · Tableau |
| Other Tools | Minitab · SPSS · MSProject · Primavera · Figma · Adobe Photoshop |