Ibrahim Radwan

Associate Professor Ibrahim Radwan

Machine Learning | Artificial Intelligence | Computer Vision

University of Canberra, Australia

Teaching Philosophy

My teaching philosophy aims to achieve effective learning outcomes by engaging students in an interactive environment. I build my strategy by providing a reasonable theoretical background of the topic and helping students implement their understanding through practice and discussion. My teaching strategies revolve around four key factors:

Students

As an educator, I need to know my students' backgrounds, previous teaching experiences, and aims when enrolling them in my units.

Content

I ensure that the prepared course content matches the unit's learning outcomes, is up to date, covers both theoretical and practical aspects of the topic, and is easily digestible by the students.

Environment

I always strive to create a comfortable yet challenging environment to facilitate interaction between myself and the students and achieve high learning standards.

Teaching Methods

I understand that students learn differently, and I utilize multiple teaching methods and modes of instruction (visual, auditory, and read/write) in the classroom.

Courses Taught

I mainly teach Data Science and Computer Vision subjects at the University of Canberra, where the Introduction to Data Science unit serves as the entry point for Master of Data Science students, and the Data Science Technology and Systems and Computer Vision and Image Analysis subjects are at the exit level (i.e., the final semester for MITS and MDS students).

Current Courses (University of Canberra)

Course Period
Computer Vision and Image Analysis (11376) 2024, S1 & 2025, S1
Computer Vision and Image Analysis G (8890) 2024, S1 & 2025, S1
Introduction to Data Science (11372) S2,2019 – S1,2025
Introduction to Data Science G (11516) S2,2019 – S1,2025
Data Science Technology and Systems (PG) S2,2021 – S2,2024

Previous Courses (Zagazig University, Egypt)

Student Supervision

Current PhD Students

Student Role Period Thesis Title
Pritesh Contractor Primary supervisor 2024-2028 Decoding Social Interactions: Advancing Visual Recognition of Human Relationships and Dynamics
Adnan Adnan Co-supervisor 2024-2028 Exploring AI Automation, decision making and its cognitive abilities
James Ireland Co-Supervisor 2021-2025 An Automatic Non-Invasive Array of Sensors for the Tracking of Tools and Materials Used in Procedural Operations

Former PhD Students

Student Role Period Thesis Title
Ravikiran Parameshwara Primary supervisor 2021-2024 Determining Affect Intensity on a Continuous Range
Soujanya Narayana Co-Supervisor 2021-2024 Joint Spatio-Temporal Modelling of Human Mood and Emotion