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    Eze Peter

    Research Fellow, AI for Decision Support (Health) at the University of Melbourne

    Peter Eze is a highly motivated individual with a focus on problem-oriented research and customer-facing solution design utilizing AI, deep machine learning, and software engineering, particularly specializing in Data Science for Computer Vision.

    His skill set includes Object-Oriented Programming (OOP) design implemented in Python and Java, with proficiency in tools like OpenCV, Tensorflow, Scikit-Learn, Pandas, and Pytorch. He is experienced in utilizing git for version control and cloud-based machine learning solutions on AWS and Microsoft Azure.

    Peter has a rich project background, having worked on diverse projects like health information systems, asset management systems, home automation systems, and more, employing agile software development methodologies. In these projects, he not only lead teams but was also actively involved in coding and project management.

    In managerial capacities, Peter has taken on technical project management and supervisor roles, handling teams of various sizes and utilizing project management tools like Atlassian's Confluence, Trello, JIRA, Hipchat, and bitbucket. He excels in interpersonal communication, risk management, and control.

    His educational journey includes pursuing studies in Computer Science at different levels, achieving distinctions and first-class honors in various courses.

    Peter Eze has a rich professional history, having been involved in organizations like Crayon, where he served as Technical Manager and other roles in software development and project management capacities.

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    Location

    Parkville, Victoria, Australia