Professional Portfolio
I design systems that connect research, data, technology, and people.
My work spans clinical and neuroscience data infrastructure, digital health, artificial intelligence, product strategy, and open science.
Across these projects I tend to work on the same kind of problem: taking something complex and fragmented, identifying the underlying structure, and designing a system that can become usable, scalable, and measurable.
Featured Systems
Three systems I designed end to end
Clinical Research Infrastructure · Health Data · Regulatory Data Systems
Clinical Data Fabric
Research Semantic Operating System (RSOS)
From heterogeneous clinical data to traceable, submission-ready datasets.
A clinical data platform that ingests heterogeneous source systems, standardises them into a canonical schema, validates and corrects records with downstream propagation, and produces traceable SDTM/ADaM outputs.
What I designed
- Canonical clinical data model
- Multi-source ingestion architecture
- Semantic mapping and inference
- Unit normalisation and derived variables
- Validation engine
- Correction with downstream impact analysis
- End-to-end provenance and lineage
- SDTM / ADaM / Define-XML exports
- REST API and role-based access control
- Natural-language interaction layer
- Zero third-party runtime dependencies
- CI across Python 3.11–3.13
My role: System Architecture · Data Modeling · Product Strategy · Clinical Data Standards · Engineering
Neuroscience Data Infrastructure · Open Science
N-DOS
Making laboratory neuroscience data easier to organise before it reaches community standards.
A framework for organising neuroscience data across the research lifecycle. Standards such as BIDS and NWB are extremely valuable, but research data often becomes inconsistent long before it reaches the stage where those standards apply.
What I designed
- Laboratory-level research data architecture
- Metadata conventions and data lifecycle structure
- Validation mechanisms and provenance tracking
- Project scaffolding and FAIR-oriented documentation
- BIDS/NWB interoperability strategy
- Python automation utilities
My role: Concept Development · Research Infrastructure · Technical Architecture · Open Science Strategy
Digital Health · Physiological Sensing
Recovery Intelligence
Turning physiological signals into interpretable recovery insights.
Explored how wearable and behavioural data could be combined with evidence-based interventions to help people understand stress, recovery, sleep, and resilience.
Product components
- Physiological data ingestion
- Recovery metrics and longitudinal tracking
- Personalised recommendations
- Behavioural interventions
- User-facing insights
- AI-supported personalisation
HRV · Sleep · Behaviour · Recovery · Heat/Cold Exposure · Wearables
My role: Research Strategy · Product Strategy · Measurement Framework · User Journey Design · Pilot Design
AI & Product Development
Applied product work
AI Commerce · Product Strategy
Brave Eagle
AI-enabled commerce products focused on recommendation systems, intelligent product discovery, multimodal search, personalisation, and automated product enrichment.
Selected product areas
Recommendation Engine · Multimodal Search · AI Product Tagging · Personalisation · Product Analytics
My contribution: Product strategy · User requirements · Customer discovery · Pilot design · Measurement frameworks · Cross-functional coordination · Commercialisation
Behavioural Design · Human–AI Interaction
Sudoforge
An independent venture exploring how physical productivity tools and digital intelligence can work together rather than compete for attention.
The first products use structured paper-based planning to support focus and deep work, while the longer-term platform explores scan-to-dashboard workflows, behavioural metrics, and AI-supported reflection.
Products
Focus Sprint Planner · Deep Work Planner · AI Companion (in development)
My role: Co-founder · Product Strategy · Behavioural Design · UX · Commercialisation
Research Infrastructure & Open Science
I don’t only design systems — I work on what makes people adopt them
The Neuro
BIDS-inspired data organisation · NAS restructuring · metadata · reproducibility · Python workflows
Pre-COSYNE Brainhack 2025
Open-source neuroscience · community infrastructure · DANDI · DataJoint · Mila
Open Brain Institute
Researcher onboarding · platform adoption · workflow design · documentation · community strategy
From Architecture to Adoption
How I work
Understand the system
What problem is actually being solved? Who experiences it? Where does the current workflow break?
Structure the problem
Users · data · workflows · constraints · dependencies · standards
Design the architecture
Data models · system boundaries · workflows · interfaces · governance
Build & validate
Prototype · test · measure · document · identify failure modes
Design for adoption
User experience · implementation · onboarding · communication · incentives
Connect to impact
Research outcomes · clinical utility · business value · scalability
My work rarely stops at the technical architecture. I am interested in what makes a system usable, trustworthy, adoptable, and valuable in the environment where it will actually operate.
Selected Community & Program Work
Building communities around systems
Brainhack Pre-COSYNE
Research infrastructure and open-science community
Réseau Sommeil
Research-network engagement and wearable sleep technology
Neuromatch Academy
Global scientific education and open neuroscience
PAINtalks
Scientific community building, sponsorship and partnerships
Interested in the architecture behind one of these projects?
Some project repositories and technical materials remain private because they contain original system designs and commercial work. I am happy to walk through selected architecture, product decisions, research methods, and implementation details in an interview or collaboration discussion.