University of Saskatchewan, Canada.
Golshid Ranjbaran is a PhD Candidate in Computer Science at the University of Saskatchewan (USASK), specializing in Artificial Intelligence, Machine Learning, and Interpretability. With a Bachelor's degree in Software Engineering and a Master's in Artificial Intelligence from the Science and Research Branch in Iran, he has accumulated several awards, including the Best Paper Award at the IKT Conference in 2021 and Best Researcher at ITRC in 2022. Golshid's research is aimed at advancing AI methodologies and improving machine learning models for real-world applications. He was also a research associate at the Data Science & Big Data Lab in Seville, Spain, in 2023. 🌐
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Education 🎓
Golshid holds a Bachelor's degree in Software Engineering and a Master's degree in Artificial Intelligence from the Science and Research Branch in Iran. He is currently pursuing a Ph.D. in Computer Science at the University of Saskatchewan (USASK), Canada, where he focuses on AI, machine learning, and interpretability, aiming to bridge the gap between theoretical advancements and practical applications.
Experience 🏢
Golshid has been awarded several prestigious positions and accolades, including a research position at the Data Science & Big Data Lab in Seville, Spain (2023), and was recognized as the Best Researcher at ITRC (2022). He has also contributed to various consultancy projects and industry collaborations, such as working on AI systems at ITRC, smart meters algorithms, and data governance in Iran.
Research Interests 🔍
Enhancing model interpretability through methods like SHAP.
Exploring sentiment analysis for stock market prediction.
Developing augmented techniques for unbalanced tasks in the financial domain.
Improving network security through Moving Target Defense technology.
Investigating Federated Learning for wearable health devices and ontology-based text summarization for efficient information processing.
Awards 🏆
Best Paper Award at the IKT Conference (2021)
Best Researcher Award at the Iran Telecommunication Research Center (ITRC) (2022)
Research Position at the Data Science & Big Data Lab in Seville, Spain (2023)
Nomination for the Gala GSA Award at the University of Saskatchewan (2025).
Selected Publications 📚
C-SHAP: A Hybrid Method for Fast and Efficient Interpretability – Applied Sciences (Q2 Journal), Published 2025.
Leveraging Augmentation Techniques for Tasks with Unbalancedness within the Financial Domain – EPJ Data Science (Q1 Journal), Published 2023.
Investigating Sentiment Analysis of News in Stock Market Prediction – International Journal of Information and Communication Technology Research, Published 2024.
Unsupervised Learning Ontology-Based Text Summarization Approach with Cellular Learning Automata – Journal of Theoretical and Applied Information Technology, Published 2023.
Analyzing the Effect of News Polarity on Stock Market Prediction – Proceedings of the 12th International Conference on Information and Knowledge Technology (IKT), Published 2021.