Morteza Saberi

Dr. Morteza Saberi is a Visiting Fellow at the School of Business, UNSW Canberra, where he previously held the position of Lecturer (Assistant Professor). Earlier in his career, he served as a Lecturer in the Department of Industrial Engineering at the University of Tafresh. He earned his PhD, with his dissertation securing first place in the competition at the Sixth International Conference on Industrial Engineering and Operations Management (IEOM) in 2016. Saberi's academic journey also includes visiting positions, such as at Curtin University and the Hasso Plattner Institute via a DAAD visiting fellowship in 2015.

His research specializations include business intelligence, data mining, applied machine learning, and data science, focusing on developing models to identify patterns in data for informed decision-making in industries like agriculture, mining, pharmaceuticals, and retail. Examples encompass predicting abnormal milk temperature using sensors and analytics, and optimizing stock allocation based on customer preferences. Saberi has authored over 150 papers in leading journals such as Computers & Industrial Engineering, Future Generation Computer Systems, and Knowledge-Based Systems. Notable publications are 'Support vector regression with chaos-based firefly algorithm for stock market price forecasting' (Applied Soft Computing, 2013), 'ZBWM: The Z-number extension of Best Worst Method and its application for supplier development' (Expert Systems with Applications, 2018), and 'Integration of artificial neural networks and genetic algorithm to predict electrical energy consumption' (Applied Mathematics and Computation, 2007). His scholarship has amassed over 7,000 Google Scholar citations with an h-index exceeding 27. He has garnered more than 20 awards, including Innovation Connection grants ($205,000 in 2021, $78,000 in 2019), a 2016 UNSW Postdoctoral Rector Fellowship ($300,000), recognition as Australia's leading researcher in Evolutionary Computation (2019), and multiple best paper and researcher accolades.