Helia Shamszadeh

Helia Shamszadeh

I’m Helia Shamszadeh, a Computer Engineering graduate from IUST. I’m passionate about data science and machine learning. I work as a Data Scientist at Ferrum Capital, developing models for financial risk prediction.

About

My name is Helia Shams Zadeh Amiri, and I am currently completing my Bachelor of Science in Computer Engineering at the Iran University of Science and Technology (IUST) in Tehran. From the early stages of my academic journey, I have been deeply interested in how data and algorithms can reveal structure, meaning, and intelligence within complex systems. This curiosity gradually led me toward data science, machine learning, and natural language understanding — areas where I now focus my academic and professional efforts.

During my undergraduate studies, I have had the opportunity to explore a wide range of fields — from computer vision and artificial intelligence to semantic knowledge representation and bioinformatics. My undergraduate thesis, “Transforming Text into Structured Knowledge: A Frame-Semantics and RDF-based Approach,” reflects my growing interest in bridging language, logic, and computation to create interpretable AI systems. I believe that developing models capable of understanding and structuring unstructured data is key to advancing both research and real-world applications.

In parallel with my studies, I have worked as a Data Scientist at Ferrum Capital (Baku, Azerbaijan), where I apply statistical learning and predictive modeling to credit scoring and financial risk assessment. This experience has helped me translate theoretical insights into production-ready systems and strengthened my commitment to developing reliable and explainable AI methods.

Beyond research and development, I have served as a Teaching Assistant in several core computer science courses, including Computer Vision, Operating Systems, Data Structures, and Theory of Automata. These teaching experiences have honed my ability to communicate complex concepts clearly and have deepened my appreciation for collaborative academic environments.

I am fluent in English (IELTS Band 8.0) and have working knowledge of German and French, which enables me to engage with international research communities and literature. I enjoy exploring interdisciplinary applications of artificial intelligence — particularly where computation meets language, cognition, and knowledge discovery.

Looking ahead, I aspire to pursue graduate research in machine learning, data mining, and natural language processing, focusing on the design of adaptive, transparent, and semantically aware AI systems. My long-term goal is to contribute to research that enhances the interpretability and fairness of machine learning while bridging academic inquiry and industrial innovation.

This page provides a brief overview of my academic and professional background. For detailed information on my education, research, and projects, please refer to my Curriculum Vitae.