National Taiwan Ocean University - Taiwan
AUTHOR PROFILE
SCOPUS
GOOGLE SCHOLAR
EARLY ACADEMIC PURSUITS
Seyed Mohammad Esmaeil Pourmohammad Azizi began his academic journey in mathematics, earning a Bachelor's degree from the University of Mazandaran in 2015 with a GPA of 16.64/20. He continued his studies with a Master’s degree at Allameh Tabataba’i University, Tehran, where he graduated in 2018 with a GPA of 17.69/20. Currently, he is pursuing a Ph.D. in Artificial Intelligence at the Department of Electrical Engineering and Computer Sciences at National Taiwan Ocean University, focusing on Smart Tele-Communication.
PROFESSIONAL ENDEAVORS
Pourmohammad Azizi has gained significant professional experience as an algorithm designer for a Fin-tech company in 2020 and 2021. Additionally, he has been actively involved in Forex Trading since 2018. His professional growth is further enriched by academic visits to Lisbon University in Portugal and Guangzhou University in China.
Pourmohammad Azizi’s research contributions are extensive and cover a range of topics in machine learning and financial mathematics. His work includes publications on Dynamical System Decomposition of Signal Learning, Deep Learning Detection for Massive MIMO Systems, Time series analysis and Volatility Forecasting using Artificial Neural Networks. He has also explored Neutrosophic Fuzzy Decision-Making and the application of machine learning in financial decision-making.
IMPACT AND INFLUENCE
His research has made significant impacts in the fields of financial mathematics, machine learning, and artificial intelligence. His contributions to Deep Learning Detection with Probabilistic Tabu Search for Massive MIMO Systems Time series analysis and the integration of machine learning in financial decision-making are widely recognized.
ACADEMIC CITATIONS
Pourmohammad Azizi's work is well-cited in the academic community, reflecting the interdisciplinary influence and relevance of his research. His Google Scholar profile indicates a robust citation record, underscoring his academic impact.
LEGACY AND FUTURE CONTRIBUTIONS
Pourmohammad Azizi aims to continue advancing the fields of smart communications, machine learning, and computational mathematics. His ongoing projects and future research endeavors, such as new models for time series forecasting and exploring dynamical systems in machine learning, promise to contribute significantly to these domains.
NOTABLE PUBLICATIONS
An Optimized Method for Solving Membership-based Neutrosophic Linear Programming Problems 2022(2)
Hybrid Approach for Forecasting Stock Exchange Index Combining Statistical Methods and Artificial Neural Network 2021(1)
Neutrosophic Fuzzy Decision-Making Using TOPSIS and Autocratic Methodology for Machine Selection in an Industrial Factory 2024
DeepEigen-Tabu: Deep Eigen Network Assisted Probabilistic Tabu Search for Massive MIMO Detection 2024