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Hyper-Planes in GLSTSVM-CIL
gravity-presentation in GLSTSVM-CIL

Data Science Researcher
Specializing in Imbalanced Data & Natural Language Processing

Passionate about extracting insights from complex data, with a proven track record in novel
machine learning approaches and a keen focus on the future of AI language.

About Me

I am a highly motivated Data Science Reseacher with a Master of Data Science degree from Ferdowsi University of Mashhad, where I graduated with honors. My academic journey culminated in a groundbreaking thesis titled "Gravitational Support Vector Machine for Class Imbalance data," which introduced a novel method based on Twin SVM to address the challenges of unbalanced datasets.

My first research was accepted at the 5th National Conference of Informatics of Iran, where I presented my paper, "Prediction of Chronic Diseases with Gravitational Support Vector Machine." This experience solidified my expertise in applying advanced machine learning techniques to real-world problems.

I am now passionately pursuing further studies and research in Natural Language Processing (NLP). My goal is to harness the power of language models and computational linguistics to understand the exciting world of artificial intelligence.

Research & Specializations

Gravitational Support Vector Machine for Class Imbalance data

Master's Thesis, FUM University - Defended with Honors

This thesis introduced a novel Twin SVM-based algorithm designed to improve classification performance on datasets with highly imbalanced class distributions. The "Gravity" concept enhances the SVM's ability to learn from minority classes more effectively.

Prediction of Chronic Diseases with Gravitational SVM

Presented at the 5th National Conference of Informatics of Iran

This paper showcased the practical application of the Gravitational weighting method in Twin SVM for predicting chronic diseases, demonstrating its superior performance compared to traditional methods on real-world medical datasets.

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