About

Welcome to the carecodeconnect home page! 🤗

“Building persuasive technologies with AI and Machine Learning for health, well-being & sustainability”

We combine the tools of social science and data science to build solutions to complex social problems.

Decode the matrix of human relations with technology: by linking computation with interpretation, we tell the human stories behind the data.
Build machine learning solutions to create caring futures: a data revolution that is equitable, fair, and sustainable. Our solutions are infused with care, ethics, privacy. We are sensitive to cultural, geographical, historical circumstances, social contexts and differences that make a difference.
Apply cutting-edge free and open source technologies to put people at the heart of the data: creating evidence-based decision-making and actionable ‘outsights’ to make the world a better place.

In short, we care, code, connect.

Explore our blog and projects to find out more!

Recent Projects

Building robust and reliable LLM/SLM AI assistant to help freelancers find high quality gigs @ Shoutt International.
Automated data analytics, causal inference, and predictive models for enhancing eco-driving behaviours @ Lightfoot.
Built interactive meditation assistant providing personalised guidance using voice and brain signals for enhanced well-being @ Data Science Retreat.

Expertise in scientific research, education, mentoring and project leadership. Skilled in research, model development, deployment, evaluation, and monitoring across the lifecycle of data products.
Advanced expertise building persuasive technologies to create behaviour change in the health, well-being, and sustainability domains. Deep expertise in causal inference and experimentation and building ML and AI systems for predictive analysis and generation of text, language, and talk-in-interaction, informed by cutting-edge human-computer interaction research on people’s use of digital technologies.
Applies best practices in software engineering - functional and object-oriented programming, testing, version control - to Machine Learning and AI production pipelines at scale.
User and product sense with research-based skillset combining conceptual, critical thinking and communication skills with scientific, programming, and engineering skills.

Documentation (Jupyter, Quarto, Sphinx), version control (git/GitHub), testing (PyTest), CI/CD (GitHub Actions), containerisation (Docker)