Key Research areas
Our Research objective is to comprehensively address failure conditions in AI-vision systems using simulation, ensuring robustness and reliability
Designing XR & VR for Simulation
We design extended reality (XR) and virtual reality (VR) solutions that integrate with virtual simulation, focusing on applications in robotics, automotive, and drone technologies. Our immersive designs help accelerate innovation, training, and real-world performance.
Photorealism and Sensor design
We craft highly photorealistic environments and engineer virtual sensors that mimic real-world behaviour with high precision using real-world data Augmentation and GenAI. This enables accurate testing of AI perception systems under a wide range of conditions, bridging the gap between simulation and reality
Edge case modelling
Our research focuses on creating rare, unexpected, and critical scenarios, the edge cases that challenge autonomous robotic vision systems the most. By simulating the unpredictable, we help in building smarter AI capable of handling the real world's toughest situations.
Vision perception network design and training
We develop and train advanced vision perception networks, enabling machines to see, understand, and react with human-level awareness. Our work pushes the boundaries of neural network design to improve detection, segmentation, and decision-making under complex conditions.
Immersive data generation
We generate rich, immersive datasets that capture the full complexity of real-world environments. This synthetic data powers faster, safer, and more scalable AI training, accelerating the journey from simulation to real-world deployment.
Human Behaviour modeling
We specialize in advanced human behavior modeling to create realistic, responsive virtual agents that mimic real-world actions, decisions, and interactions. Our technology allows us to simulate how individuals and crowds move, react, and adapt in complex environments