Peter is a Doctoral Researcher in Clinical Neuroscience at the University of Turku and an MBA candidate at Johns Hopkins Carey Business School. His research sits at the intersection of AI, translational neuroscience, and global health systems. As founder of the Pan-African AI Health Initiative (PAAHI), he leads efforts to develop reproducible, trust-calibrated AI systems for TBI, rabies, and malaria diagnostics.

He is the architect of EvidenceOS, a modular operating system for confidence-calibrated evidence synthesis, and the NeuroFusion Pathway, a multimodal framework for precision TBI classification. His work integrates domain-adapted AI models, conformal prediction, and federated deployments to enable scalable impact in both high-resource and LMIC contexts. He contributes to six NINDS TBI Working Groups and is aligning his research with the future of global neurotrauma classification and evidence infrastructure.

My research develops modular, AI-driven frameworks for global neurotrauma decision support—centered on TBI phenotyping, biomarker harmonization, and LMIC-relevant deployment. I focus on scalable, trust-calibrated methods integrating neuroimaging, molecular biomarkers, clinical variables, and psychosocial modifiers. Key projects include: (1) NeuroFusion Pathway, a precision classification pipeline for TBI using multimodal data and conformal prediction; (2) EvidenceOS, a confidence-calibrated evidence synthesis platform for biomarkers and outcome metrics; and (3) Clinimetrics AI, a benchmarking engine for clinical AI in over 135 specialties, emphasizing uncertainty quantification and regulatory transparency. My work supports six NINDS Working Groups and the InTBIR Living Reviews initiative.

I provide mentorship and guest lectures on the following topics:
- AI and machine learning in clinical neuroscience
- Evidence-based digital health infrastructure
- Systematic review automation and reproducibility
- Responsible AI development for low-resource contexts
- Translational methods for biomarker and outcome modeling

I support MSc and PhD student supervision, including LMIC-focused NLP and AI projects, with an emphasis on scalable, clinically aligned deployment strategies.