Quantitative Analyst | PhD Candidate in Econophysics | Financial Modeling | Machine Learning | Algorithm Design | NN | LLM
I am an experienced Quantitative Analyst and a Ph.D. candidate in Econophysics at Shahid Beheshti University with a strong foundation in theoretical physics and applied mathematics. My unique background bridges rigorous academic research with hands-on industrial experience in financial markets.
Key Strengths:
1. Advanced Mathematical & Analytical Thinking
Expertise in probability theory, stochastic processes, linear algebra, and time-series analysis. I develop and validate predictive models that capture complex market behavior.
2. Algorithm Design & Programming Proficiency
Proficient in designing robust algorithmic solutions and translating them into production-level code using Python (NumPy, pandas, Scikit-learn, TensorFlow), MQL, and Mathematica. Experience includes algorithmic trading, risk modeling, and portfolio optimization.
3. Machine Learning, Neural Networks (NN), and LLMs
Skilled in applying machine learning techniques and deep learning architectures such as LSTM, CNN, transformers, and large language models (LLMs) for forecasting, anomaly detection, and financial text analysis.
4. Research & Problem-Solving
As a physicist and published researcher, I solve complex problems by integrating mathematical modeling (e.g., LPPLS for bubbles) with empirical financial data to create actionable insights and intelligent systems.