Associate ProfessorAsef Nazari

Associate Professor

Faculty of Science Engineering and Built Environment/School of Information Technology

  • Associate Professor
    Faculty of Science Engineering and Built Environment/School of Information Technology
  • +61 3 522 78674 (Work)
  • Geelong Waurn Ponds Campus, 75 Pigdons Road, Waurn Ponds, Victoria 3216

TEACHING EXPERTISE

My teaching philosophy is based on the opinion that education is a transformative force, capable of reshaping individual destinies and society at large. I envision education as a bridge that extends beyond the borders of traditional classrooms, reaching into the vast expanse of the real world where theoretical knowledge is put into practice. I am dedicated to nurturing a synergetic relationship between academic subjects and the professional aspirations of my students. To achieve this, I endeavor to cultivate a dynamic learning atmosphere that promotes not just participation, but active engagement. I encourage my students to embrace critical thinking and improve their problem-solving skills, equipping them with the confidence and competence to navigate the complexities of life and their future careers. In essence, my role as an educator is to guide students on a journey of discovery, where learning is not merely an academic exercise, but a lifelong quest for growth, understanding, and the application of knowledge in all its forms.

As an experienced educator, I have been at the forefront of mathematics and statistics education for over two decades. My pedagogical approach is deeply rooted in my teaching philosophy, which emphasises the practical application of academic knowledge in real-world scenarios. Since 2020, I initiated the development of an innovative master's-level unit, Mathematics for AI. This unit is meticulously crafted to communicate the essential mathematical concepts that form the backbone of AI and machine learning. My curriculum is not only grounded in theory but is also enriched with tangible insights drawn from my extensive industrial experience and research publications. My commitment to education is further exemplified by my approach to assessment design. I create assessment items that are not just intellectually stimulating but also deeply engaging and reflective of real-world challenges in AI and data analytics. These assessments are designed to not only test the students' knowledge but also to inspire them to think critically and apply their learning in practical, impactful ways fostering their employability.

TEACHING ACTIVITIES

  • CURRENT DOCTORAL SUPERVISION
    Soft Happy Colouring and Community Structure of Networks
    Mohammad Hadi Shekarriz - School of Information Technology
  • CURRENT DOCTORAL SUPERVISION
    An Artificial Intelligence-Empowered Framework for Mitigating the Impacts of Data Poisoning in Identity Authentication
    Alireza Mohammadi - School of Information Technology
  • CURRENT DOCTORAL SUPERVISION
    Sustainable Multi-Project Scheduling Under Uncertainty
    Mohammad Ghasemi - School of Information Technology
  • CURRENT DOCTORAL SUPERVISION
    Analysis of Optimal Performance of Renewable Energy for Electric Vehicles through Data-Driven Approaches
    Zohreh Moghaddas - School of Information Technology
  • CURRENT DOCTORAL SUPERVISION
    Robust Distributed Coordination of Electric Vehicle Charging and Discharging in Modern Power Distribution Networks
    Muhammad Ismail - School of Information Technology
  • CURRENT DOCTORAL SUPERVISION
    Sim-to-Real Transfer for Robotic Deep Reinforcement Learning
    David Azimi - School of Information Technology
  • CURRENT DOCTORAL SUPERVISION
    Artificial Intelligent-Enabled Circuit for Identification of Defects in Solar Panels
    Ali Ghahremani - School of Engineering
  • CURRENT DOCTORAL SUPERVISION
    Deep Learning Based Multi Modal Cyberbullying Detection
    Weiqi Zhang - School of Information Technology
  • CURRENT DOCTORAL SUPERVISION
    Integrating Backup Energy Systems into Renewable Hybrid Microgrids for Remote and Off-Grid Applications
    Ali Asghari Gorji - School of Information Technology
  • COMPLETED DOCTORAL SUPERVISION
    Exploring Taxonomy-driven Machine Learning Models for Enhancing Multi-level Hierarchical Classification
    Tanya Boone Sifuentes - School of Information Technology - 2024
  • COMPLETED DOCTORAL SUPERVISION
    Analysis of Cryptocurrency Price Movements: A Hybrid Machine Learning Approach
    Rasoul Amirzadeh - School of Information Technology - 2024
  • COMPLETED DOCTORAL SUPERVISION
    Machine Learning-Based Surrogate Models for Scenario Discovery of Sustainable Land-Use Futures
    Md Shakil Khan - School of Life and Environmental Sciences - 2025
  • COMPLETED DOCTORAL SUPERVISION
    Inclusion of Prior Knowledge With Deep Neural Networks for Enhancing Performance and Rule Consistency
    Shashank Gupta - School of Information Technology - 2024