My Expertise
Applied AI in human factors
Biography
Mohammed Hossny received his bachelor degree in computer science from Cairo University. He earned his masters degree in computer science in collaboration with the IBM Centre of Advance Studies (CAS). Later, he joined the Institute for Intelligent Systems and Research Innovation (IISRI) at Deakin University and developed an algebraic framework for multimodal image fusion as part of his PhD degree. He is currently a senior lecturer at the...view more
Location
ORCID as entered in ROS
https://orcid.org/0000-0002-1593-6296
Related Links
Digital mannequins win Engineering Gold for IISRI
Deakin researchers have been rewarded for high-tech innovation in automotive design. A system that uses digital mannequins and computer-generated vehicles to assess the comfort of drivers has been awarded the 2016 Society of Automotive Engineers (Australasia) Mobility Engineering Exc...
Lockheed Martin Partners With Deakin University To Further Develop Industrial Exoskeleton
“The innovative work done by Dr. Mohammed Hossny and his team at Deakin’s IISRI extends the technological foundation for the FORTIS Exoskeleton with the potential for a broad range of applications across the defense, automotive and mining industries.”
Vox Lumen ready to shine at White Night Melbourne
Crowds at Federation Square during this weekend’s White Night Melbourne will have the chance to influence and interact with a large-scale art installation, thanks to the cutting-edge work of Deakin University’s Motion.Lab and Centre for Intelligent Systems Research (CISR).Videos
The VoxelScape #LiDAR #dataset is released (links below). The dataset includes 100K samples of simulated 64-channels #velodynelidar #pointclouds, labels, intensity and bounding boxes. Intensity (from real data) is at the sub-mesh level and is driven by #PBR #material #shaders. Labels are at object and mesh levels. The dataset features a wide variety of vehicles, pedestrians, vegetation, roadwork setups, buildings and procedurally generated #urban landscapes. This is a great collaboration with Khaled Saleh, Ahmed Abobakr, Attia Mohammed and Julie Iskander.
Check out how our refined #rl continuous control via parameterised Tanh performs on the #OpenAI #GYM problems. Paper: https://bit.ly/3oCJIQH
A great collaboration with Julie Iskander, Attia Mohammed and Khaled Saleh. #AI #ML #ArtificialIntelligence #MachineLearning #DeepLearning #MLP#researchpaper #Control #DRL #reinforcementlearning #research #RL #signal
A great collaboration with Julie Iskander, Attia Mohammed and Khaled Saleh. #AI #ML #ArtificialIntelligence #MachineLearning #DeepLearning #MLP#researchpaper #Control #DRL #reinforcementlearning #research #RL #signal
Check out how our #AI #rl agent handles different types of noise while maintaining a standing posture. The agent was trained on levelled ground with no noise and was able to accommodate different noise sources. A great collaboration with Julie Iskander.
Value misalignment strikes back [1]. This AI agent learned to walk backwards to prolong not falling. A great collaboration with Julie Iskander.
Links
[1] https://bit.ly/3lktTfr
Links
[1] https://bit.ly/3lktTfr
Check out how our #AI #rl agent handles different types of noise while maintaining a standing posture. The agent was trained on levelled ground with no noise and was able to accommodate different noise sources. A great collaboration with Julie Iskander.
VoxelScape Dataset
AI learns Refined Control
An AI agent achieves postural balnace
Value misalignment strikes back
An intoxicated AI agent learns to stand with noisy states and actions