Amir Saberi

Research Fellow

Picture of Amir Saberi

Brian Anderson Building (115), A302


Google Scholar



Online optimisation, control theory, machine learning, information theory, renewable energy, food science, python, MATLAB.


Dr Saberi works on making machine learning systems more robust to uncertainties and dynamic environments. His aim is to establish reliable baselines for data analysis and data-driven decision-making strategies. The fields relevant to his research are online optimisation, control theory, machine learning, and information theory.


Dr Saberi is a data scientist/electrical engineer with more than three years of experience in analysing data in computer networks, food science, and renewable energy. He is a professional programmer in Python and MATLAB and has experience in working with Splunk, SQL, and data visualization tools. With a background in electrical engineering, Dr Saberi has gained technical knowledge through various engagements at the higher education level in Statistic and Machine Learning, Dynamic Programming and Information Theory, Telecommunications and Control Systems, and Renewable Energies resulting in several publications and prizes. He completed his PhD at the University of Melbourne in 2021, his Ms at the University of Tehran in 2014, and his BSc at the University of Tabriz in 2011.

Activities & Awards

  • CSIRO STEM Professional in Schools volunteer
  • Vice-Chair & Treasurer for the IEEE student branch at the University of Melbourne 2018-2021

For more details, please see this link.

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