Parsa Abbasi is a graduate student in Artificial Intelligence at Iran University of Science and Technology, where he conducts research focused on enhancing graph attention networks for relational graphs. His research aims to advance existing architectures like RAGAT by proposing and developing a model with fewer training parameters to prevent overparameterization. Additionally, he explores dynamic attention mechanisms to effectively capture the relational information within the graph.
Parsa received his BSc in Computer Engineering from the University of Guilan, where he explored areas such as natural language processing and deep learning. During his undergraduate studies, Parsa co-authored a research paper on designing sentiment analysis models using deep learning architectures for low-resource Persian language.
Driven by his passion for the field, Parsa seeks to pursue a PhD in AI to continue his research and further advance the field.
MSc in Artificial Intelligence, 2020 - Ongoing
Iran University of Science and Technology
BSc in Computer Engineering, 2015 - 2019
University of Guilan
python (proficient), java (experienced), matlab and c++ (amateur)
keras, pytorch, scikit-learn, imbalanced-learn, h2o
numpy, pandas, plotly, matploblib, sql
Throughout his academic journey, he has completed various online courses. However, in recent years, he has been relying on several learning resources, such as Youtube videos, online articles, academic papers, and books, to acquire knowledge.