Ibrahim Radwan

Associate Professor Ibrahim Radwan

Machine Learning | Artificial Intelligence | Computer Vision

University of Canberra, Australia

Research Interests

My research focuses on developing AI systems that can understand and interpret complex human behaviors and interactions in real-world environments. Specifically, my work spans:

Computer Vision

Developing robust algorithms for human pose estimation, action recognition, and visual understanding in complex environments with occlusions.

Human-Centered AI

Creating AI systems that understand human behavior, emotions, and physiological responses for healthcare, safety, and human-computer interaction.

Multimodal Data Fusion

Integrating information from multiple sensors (visual, audio, physiological) to improve understanding and decision-making in AI systems.

Human-Object Interaction

Modeling and understanding how humans interact with objects in their environment for applications in robotics, surveillance, and assistive technologies.

Research Projects

Assistive Technologies for Young People Safety on Two-Wheelers

Funding: AUD 621,800 | Department of Infrastructure, Transport, Regional Development, Communications and the Arts | 2023-2025

Developing an intelligent sensing box equipped with AI feed algorithms to detect ambient objects on the roads and inform two-wheelers of any potential risks or hazards in the streets.

Advanced Rider Assistance Systems for Improved Road Safety of Motorcyclists

Funding: AUD 5,654,275 | Cooperative Research Centres Program | 2023-2025

Enhancing research on autonomous driving technology for two-wheel vehicles to ensure riders' safety.

GOTERRA PhD Scholarship in Robotics

Funding: AUD 112,000 | GOTERRA PTY LTD | 2023-2026

Developing novel techniques to classify inorganic matter contained in organic waste for automated recycling systems.

Using aerial imagery and computer learning to detect lignum on the floodplain

Funding: AUD 65,453.45 | Mallee Catchment Management Authority | 2022

Investigating deep learning approaches to detect the growth of lignum plants on river sides.

Research Statement

As a dedicated AI researcher, I strive to advance human-object interaction in complex environments. With a decade of experience, including roles at the University of Canberra and the Australian National University, I've significantly impacted "Human Activity Recognition," publishing 45 papers in top-tier avenues. Actively contributing to conferences and journals, I've secured over AUD 6.45M in research funding in the last three years, solidifying my position as a top-tier researcher with a focus on computational behavior analysis, aiming to contribute to the transformative potential of AI.