Rate My Professor Yaseen Hezam

Hezam's key publication is "Machine learning in predicting firm performance: a systematic review," published in 2025 in the China Accounting and Finance Review, where he is the corresponding author alongside co-authors Hoa Luong and Lilian Anthonysamy. This work conducts a systematic literature review of 70 studies from 2013 to 2023, evaluating machine learning techniques for predicting firm performance across multiple dimensions. Financial performance attributes, such as liquidity and solvency ratios, featured in 46% of studies, followed by market positioning (23%), operational efficiency (22%), innovation capability (12%), leadership quality (10%), and employee engagement (12%). Classification methods dominated predictions, particularly for financial performance (43 instances), with clustering (32 instances) and regression (22 instances) also prevalent. Leading algorithms included neural networks (27 references), logistic regression (26), decision trees (26), support vector machines (25), random forests (24), and linear regression (22). The review underscores machine learning's advantages in managing large, complex datasets over traditional statistical approaches and recommends holistic models integrating financial and non-financial predictors for enhanced accuracy. In recognition of his academic excellence, Hezam received the 2024 Alan MacGregor Prize and was named the 2024 Outstanding PhD Student at the University of Otago. His contributions are advancing data-driven insights in business and finance disciplines.