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About

Yunus Santur is a researcher at the forefront of applying artificial intelligence to financial markets, with a primary focus on algorithmic trading, deep learning, and natural language processing (NLP) in FinTech. His work centers on developing intelligent systems that can navigate the chaotic nature of financial time series, enabling more accurate price predictions and automated trading decisions. Santur’s major contributions include pioneering an ensemble learning approach combined with candlestick pattern recognition for algorithmic trading, and a deep learning-based regression model tailored for the BIST30 index. He has also explored genetic algorithms for optimizing trading strategies and created a lightweight NLP-driven text-to-chart application for financial analysis. While his most-cited paper has garnered 5 citations, his cumulative impact is growing as his innovative methods address critical challenges in financial prediction and automation. Santur’s research bridges the gap between cutting-edge AI techniques and practical trading applications, offering valuable tools for both academics and industry practitioners seeking to harness machine learning for financial gain.