Founder CEO, ChemicalQDevice
Builds open-source systems for oncology clinical trials, clinical robotics, federated learning, and physical AI safety.
This GitHub profile organizes research and engineering prototypes focused on how AI systems, robotics, clinical trial infrastructure, and regulated healthcare workflows may converge in oncology.
Responsible-use note: These repositories are R&D prototypes. They are not clinically validated, and are not intended for diagnosis, treatment, patient selection, or production clinical decision-making.
- Oncology clinical trial AI — trial workflows, eligibility screening, patient journey simulation, and sponsor-side automation.
- Physical AI for healthcare — robotics, embodied agents, digital twins, and safety-gated clinical workflows.
- Federated learning — multi-site trial learning patterns that keep sensitive data local.
- Clinical interoperability — MCP-style interfaces, FHIR/DICOM-inspired workflows, audit trails, and provenance.
- LLMs for pharmaceutical R&D — language-model workflows for oncology, drug discovery, trial operations, and evidence synthesis.
- AI safety and governance — responsible-use boundaries, validation concepts, limitations, privacy, and regulatory positioning.