AI in Medical Diagnostics
Developing explainable deep learning models for early disease detection using multi-modal imaging sources like ultrasound and MRI to provide reliable, transparent diagnostic support.
Industrial Automation
Designing intelligent control systems for predictive maintenance, quality control, and adaptive manufacturing processes to create smarter, more efficient industrial environments.
Explainable & Trustworthy AI
Creating transparent AI systems that provide interpretable explanations for their decisions, crucial for building trust and ensuring accountability in high-stakes applications.
Adaptive & Learning Systems
Developing self-tuning and reinforcement learning-based controllers that can dynamically adapt to changing system parameters and uncertain, real-world environments.
Multi-modal Data Fusion
Architecting advanced systems to combine heterogeneous data sources—such as images, sensor streams, and text—for more robust and superior decision-making.
AI for Sustainability
Applying AI to optimize energy consumption, manage natural resources, and develop intelligent systems for advanced environmental monitoring and climate technology.