University of Technology Sydney - Australia
Author Profile
SCOPUS
🎓 Early academic pursuits
Hassan Gharoun was born on 23rd july 1992 in iran. his journey into academia began with a bachelor's degree in industrial engineering with a specialization in industrial production from kharazmi university of tehran (2010–2014). following this, he pursued his master's degree in industrial engineering at the university of tehran (2014–2017), where he deepened his expertise in data-driven systems and optimization. his early academic performance and passion for analytical research laid a strong foundation for his future endeavors. although his background initially focused on industrial systems, his early interest in machine learning and applications in power electronics gradually became prominent.
💼 Professional endeavors
After completing his master’s degree, hassan contributed to the academic community through teaching, notably at the university of tehran. he served as a tutor in advanced econometrics in fall 2017, where he handled responsibilities such as mentoring projects, tutoring in time series algorithms, and grading. he also provided practical insights using sequential deep neural networks and python programming. alongside teaching, he expanded his knowledge base by engaging in international conferences and collaborations, where he actively contributed to data science and optimization research, including subjects related to power electronics and predictive modeling.
🔬 Contributions and research focus
Hassan Gharoun is currently pursuing a ph.d. in analytics at the university of technology sydney (2022–2026). his research spans several methodological domains, including data-driven AI optimization, probabilistic machine learning, meta-learning, and deep learning. these methodologies are employed in solving complex real-world problems where predictive decision-making is crucial. his application-focused research extends to fields like predictive modeling and power electronics, where data-centric models drive intelligent systems. his interdisciplinary approach enhances the integration of machine learning into classical engineering problems, bringing innovative contributions to the analytics landscape.
🌍 Impact and influence
Hassan’s scholarly impact has been marked by both national and international recognition. he received the best paper award at the international conference on industrial engineering and AI operations management held in paris in july 2018, demonstrating his capability to produce high-quality and impactful research. his teaching and mentorship in econometrics and deep learning have also positively influenced students at the university of tehran. by blending industrial engineering insights with cutting-edge analytics and applications such as power electronics, he continues to be a bridge between traditional engineering and emerging ai-driven solutions.
📚 Academic cites
Although still in the early stages of his doctoral journey, hassan gharoun has already begun establishing a scholarly footprint through academic conferences and teaching contributions. his AI recognition at an international level hints at the growing citation potential of his works. his research is expected to be cited across multiple domains, particularly in data analytics, predictive systems, and interdisciplinary applications in sectors like power electronics. as his phd progresses, the impact and citation metrics of his work are projected to increase significantly.
🚀 Legacy and future contributions
Looking ahead, hassan gharoun is poised to make significant contributions to academia and industry through the integration of analytical methods with practical applications. his ambition is to lead innovations at the intersection of deep learning and optimization, enhancing intelligent systems in fields like healthcare, energy, and power electronics. with a strong academic trajectory and international exposure, he is building a legacy rooted in methodological rigor and impactful applications. his future goals include expanding collaborative research, publishing in top-tier journals, and contributing to sustainable technological solutions globally.
Notable Publications
Title: A comprehensive bibliometric analysis on social network anonymization: current approaches and future directions
Author(s): Navid Yazdanjue, Hossein Yazdanjouei, Hassan Gharoun, Babak Amiri, Amir H. Gandomi
Journal: [No journal information available] — the source or journal name was not provided in the data you shared. If you have a DOI or additional details, I can help track it down further.