Ali Eshragh

Dr. Ali Eshragh is an Honorary Senior Lecturer at the University of Newcastle's School of Information and Physical Sciences, specializing in statistical modeling and machine learning for big data analysis. His research focuses on developing automated forecasting systems to analyze big time series data and generate accurate future predictions, with applications spanning energy demand forecasting, supply chain optimization, and pandemic modeling.

Dr. Eshragh holds a PhD from the University of South Australia and a BSc from Sharif University of Technology in Iran. His research expertise spans Time Series Forecasting (30%), Operations Research (30%), and Stochastic Analysis and Modeling (40%), as reflected in his Fields of Research codes. He has established the ForBiD (Forecasting and Big Data) research group, which has rapidly grown to include members from the University of Newcastle, University of Queensland, Monash University, UC Berkeley, and Yale University.

His publication record demonstrates a strong trajectory in applying advanced statistical methods to real-world problems, with recent work focusing on reinforcement learning for combinatorial optimization, efficient algorithms for big time series data analysis, and probabilistic modeling of complex systems like pandemics. His research bridges theoretical advances in randomized numerical linear algebra with practical applications in forecasting.

Dr. Eshragh has received the Australian Society for Operations Research 2017 Rising Star Award and has secured over $3.6 million in research funding from various sources including the Australian Research Council, Department of Education, and industry partners like Coca Cola Amatil and Sanitarium.

He actively supervises PhD and honors students in areas including reinforcement learning algorithms, big time series data analysis, and Markov decision processes. His industry collaborations with Australian food and beverage supply chains have directly motivated his academic research, reflecting his commitment to translating theoretical advances into practical solutions.