Knowledge & Innovation

Research Papers

Advancing the future of AI, robotics, and computational science through rigorous academic work.

Machine Learning

Probabilistic Models for Real-Time Decision Making

A deep exploration into probabilistic inference systems optimized for autonomous navigation, robotics planning, and uncertainty-aware predictions.

AI Systems

Efficient Transformer Architectures for Edge Devices

Research on lightweight transformer models enabling high-accuracy inference on low-power IoT and embedded systems.

Explainable AI

Interpretable Deep Learning via Feature Attribution Maps

A novel approach to explaining the internal reasoning of deep neural networks using high-resolution attribution visualization.