Dr. Zeinab Shahbazi is an accomplished researcher specializing in Reinforcement Learning, Deep Learning, Natural Language Processing, Blockchain, and Knowledge Discovery. With a Ph.D. in Computer Engineering from Jeju National University, South Korea, she has over eight years of research experience in AI and data-driven technologies. Dr. Shahbazi has held postdoctoral positions in Spain and Sweden and is currently a Senior Lecturer in AI at Kristianstad University. Her research focuses on enhancing state-of-the-art architectures and developing innovative solutions in software-based intelligent systems. She has been recognized with several academic awards, including a Presidential Award and Best Paper Presentation honors. Fluent in multiple languages and technically skilled in programming and data systems, she actively contributes as a reviewer for high-impact journals. Her international collaborations and funded research projects reflect her commitment to advancing AI applications. Dr. Shahbazi is a dedicated and forward-thinking researcher making significant contributions to the field of computer science.

Professional Profile 

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Education

Dr. Zeinab Shahbazi holds a Ph.D. in Computer Engineering from Jeju National University, South Korea, where she completed her dissertation on cryptocurrency price prediction using blockchain frameworks, graduating with an impressive CGPA of 4.32/4.5. She also earned a Master’s degree in Computer Engineering from Chonbuk National University, Korea, with a thesis on deep learning techniques for paragraph focus analysis. Her foundational education includes a Bachelor’s degree in Computer Engineering from Pooyesh University in Iran. Throughout her academic journey, she received several scholarships and honors, reflecting her consistent academic excellence. Her education has been firmly rooted in AI, software systems, and intelligent technologies, providing her with a robust theoretical and practical grounding. This strong academic background has played a pivotal role in shaping her as a multidisciplinary researcher with global exposure, capable of addressing complex problems in AI and data science with both depth and innovation.

Professional Experience

Dr. Zeinab Shahbazi has accumulated diverse international professional experience in research and academia. She is currently a Senior Lecturer in Artificial Intelligence at Kristianstad University, Sweden. Prior to this, she held postdoctoral researcher positions at Halmstad University in Sweden and at the BCN-AIM Lab at the University of Barcelona in Spain. Her work has consistently focused on applied AI, reinforcement learning, and blockchain-based systems. Dr. Shahbazi has also led and participated in international research collaborations, notably securing a Vinnova-funded international staff exchange project with a partner institution in South Korea. Her career path showcases her ability to transition between theoretical research and practical implementations, including experience in advanced programming, system architecture, and AI model development. These roles have enabled her to contribute to both the academic and industrial applications of intelligent technologies, while also strengthening her leadership and mentoring capabilities in multidisciplinary, multicultural environments.

Research Interest

Dr. Zeinab Shahbazi’s research interests are deeply rooted in intelligent computing systems, with a focus on Reinforcement Learning, Deep Learning, Natural Language Processing (NLP), Blockchain, Knowledge Discovery, and their integration within modern technological ecosystems such as IoT, edge computing, and big data platforms. Her core research ambition lies in improving existing AI models and architectures, addressing their limitations, and introducing novel components to enhance performance and applicability. She has made notable contributions to the software aspects of AI, particularly through her work on knowledge-driven systems and blockchain-based data prediction. Dr. Shahbazi combines theoretical advancements with practical implementations, bridging the gap between academic research and real-world applications. Her multidisciplinary focus reflects a keen interest in innovation, system integration, and cross-domain problem-solving. This makes her work highly relevant to both academic audiences and industry stakeholders interested in deploying intelligent, data-driven systems for practical and scalable use.

Award and Honor

Dr. Zeinab Shahbazi has received multiple awards and honors in recognition of her academic excellence and research contributions. During her Ph.D. at Jeju National University, she was awarded the prestigious Presidential Award for distinguished research publications. She also received a university research grant in 2021 for her outstanding output during 2019–2020. Earlier in her academic career, she was a recipient of the BK government scholarship and multiple semester-based scholarships during her Master’s studies at Chonbuk National University. Her early academic promise was also recognized with a government-funded scholarship during her undergraduate studies in Iran. Additionally, she won the Best Paper and Presentation Award at the ITEC Conference in 2019, further solidifying her reputation in the research community. These honors demonstrate a consistent trajectory of excellence, reflecting both the quality and impact of her research work, as well as her ability to compete and stand out in international academic environments.

Conclusion

Dr. Zeinab Shahbazi exemplifies a dynamic and impactful researcher in the field of computer science, particularly in AI, machine learning, and data-driven systems. Her strong educational background, diverse international research experience, and cross-disciplinary expertise make her a well-rounded academic and innovator. Her ability to secure research funding, collaborate internationally, and publish high-quality work underlines her potential for long-term academic leadership. Recognized through various awards and honors, she has demonstrated excellence not only in individual performance but also in contributing to the broader scientific community through peer review and collaboration. Fluent in multiple languages and culturally adaptive, Dr. Shahbazi brings global perspective and technical depth to every role she undertakes. With a forward-thinking mindset and a commitment to advancing the state of AI, she stands as a strong candidate for high-level recognitions such as the Best Researcher Award and is poised to continue making meaningful contributions to academia and beyond.

Publications Top Notes

• Title: Integration of blockchain, IoT and machine learning for multistage quality control and enhancing security in smart manufacturing
  Authors: Z. Shahbazi, Y.C. Byun
  Year: 2021
  Citations: 187

• Title: A procedure for tracing supply chains for perishable food based on blockchain, machine learning and fuzzy logic
  Authors: Z. Shahbazi, Y.C. Byun
  Year: 2020
  Citations: 140

• Title: Towards a secure thermal-energy aware routing protocol in wireless body area network based on blockchain technology
  Authors: Z. Shahbazi, Y.C. Byun
  Year: 2020
  Citations: 123

• Title: Smart manufacturing real-time analysis based on blockchain and machine learning approaches
  Authors: Z. Shahbazi, Y.C. Byun
  Year: 2021
  Citations: 72

• Title: Toward improving the prediction accuracy of product recommendation system using extreme gradient boosting and encoding approaches
  Authors: Z. Shahbazi, D. Hazra, S. Park, Y.C. Byun
  Year: 2020
  Citations: 68

• Title: Improving transactional data system based on an edge computing–blockchain–machine learning integrated framework
  Authors: Z. Shahbazi, Y.C. Byun
  Year: 2021
  Citations: 64

• Title: Product recommendation based on content-based filtering using XGBoost classifier
  Authors: Z. Shahbazi, Y.C. Byun
  Year: 2019
  Citations: 64

• Title: Agent-based recommendation in E-learning environment using knowledge discovery and machine learning approaches
  Authors: Z. Shahbazi, Y.C. Byun
  Year: 2022
  Citations: 63

• Title: Fake media detection based on natural language processing and blockchain approaches
  Authors: Z. Shahbazi, Y.C. Byun
  Year: 2021
  Citations: 63

• Title: Improving the cryptocurrency price prediction performance based on reinforcement learning
  Authors: Z. Shahbazi, Y.C. Byun
  Year: 2021
  Citations: 60

• Title: Machine learning-based analysis of cryptocurrency market financial risk management
  Authors: Z. Shahbazi, Y.C. Byun
  Year: 2022
  Citations: 58

• Title: Lithium-ion battery estimation in online framework using extreme gradient boosting machine learning approach
  Authors: S. Jafari, Z. Shahbazi, Y.C. Byun, S.J. Lee
  Year: 2022
  Citations: 58

• Title: Blockchain-based event detection and trust verification using natural language processing and machine learning
  Authors: Z. Shahbazi, Y.C. Byun
  Year: 2021
  Citations: 51

• Title: Knowledge discovery on cryptocurrency exchange rate prediction using machine learning pipelines
  Authors: Z. Shahbazi, Y.C. Byun
  Year: 2022
  Citations: 42

• Title: Lithium-ion battery health prediction on hybrid vehicles using machine learning approach
  Authors: S. Jafari, Z. Shahbazi, Y.C. Byun
  Year: 2022
  Citations: 36