A portfolio of 180+ patents spanning computer vision, healthcare AI, multimodal systems, and trustworthy AI architectures.
My patent portfolio reflects long-term research across multiple generations of AI systems, from early computer vision and multimedia retrieval to modern multimodal foundation models and verification-centric AI systems.
Rather than listing every individual patent, this page organizes inventions by technical themes and system contributions, highlighting representative innovations and their impact areas.
AI methods for radiology, clinical decision support, patient modeling, and diagnostic assistance systems.
Radiology AI Clinical Decision Support Medical ImagingEarly and modern methods for image understanding, visual retrieval, and multimodal representation learning.
Computer Vision Image Retrieval Multimodal LearningArchitectures and methods for large-scale AI systems combining language, vision, and structured data.
LLMs Foundation Models Representation LearningRecent inventions focused on verifying, correcting, and improving reliability of AI-generated outputs, especially in healthcare settings.
Verification AI Error Detection AI SafetyBio-inspired memory and reasoning architectures for persistent knowledge representation in AI systems.
Memory Models Reasoning Cognitive AIMethods for analyzing radiology images and generating structured clinical insights.
Early foundational work in visual similarity search and multimedia retrieval systems.
Techniques for identifying clinically similar patients to support treatment decisions.
Integration of imaging, text, and structured data for healthcare decision support.
Systems for detecting factual inconsistencies and correcting AI-generated clinical reports.
Recent patent activity focuses on trustworthy AI systems, particularly:
These reflect a shift from isolated model improvements toward system-level AI reliability and accountability.
For the complete and continuously updated list of patents, please refer to: