Current focus
Sloths Intel
My current focus is on founding and building Sloths Intel — an independent practice and company dedicated to developing practical, ethical AI and data systems.
The work centres on translating research-level methods into tools that operate reliably under real-world constraints, particularly for small and medium-sized organisations and resource-limited teams.
Through Sloths Intel, I explore how deliberate system design, lightweight analytics, and transparent modelling can support better decision-making, while remaining accountable, evaluable, and grounded in real use.
Selected Work
A selection of applied work showing how complex data is turned into practical, decision-ready systems. Across domains, the emphasis is on reliability, interpretability, and solutions that hold up under real-world constraints.
AutoPred: Hybrid AI for Predictive Analytics
COMING SOON...
View project site · Explore workflow and code
Find out more about how hybrid AI can support your predictive analytics needs.
AutoVisuals: Scalable Creative Automation
An automation-first pipeline for generating, enhancing, and managing large volumes of visual content with consistent quality and minimal manual intervention.
View project site · Explore workflow and code · Access sloths visuals stock
Explore how automation could streamline your creative works.
AutoTrac: Low-Friction Time & Income Tracking
A lightweight tool designed to reduce tracking friction and provide clear summaries that support planning, transparency, and sustainable work patterns.
View project site · Explore workflow and code
Try a simple approach to tracking that supports clarity and planning.
Predictive Modelling & Public Health Decision Support
Access my profile at Imperial College London
Population-scale genomic data were transformed into reliable, uncertainty-aware models to support vaccine strategy discussions, public health planning, and operational research in time-critical settings.
ISPPD2022 presentation · ISPPD2022 poster · INVAR2023 presentation · Explore workflow and code
IMMEM2025 presentation · Explore workflow and code
Explore how predictive modelling could support decisions in your organisation.Scalable Data Curation & Workflow Automation
Access my profile at Wellcome Sanger Institute
Fragmented, heterogeneous datasets were harmonised into standardised, analysis-ready assets using automated workflows that reduced manual overhead and scaled across teams and projects.
See how automated workflows can simplify and stabilise your data pipeline.
Reliable Systems Design in Next-Generation Networks
Access my profile at King's College London
Systems-level research examined coexistence, reliability, and performance under constraint in complex technical environments, shaping a robustness-first approach to system design.
View selected publications from IEEE · Explore Wikipedia citations
Learn how modern information technology could improve the reliability of your organisational data.
Interested in applying any of these approaches or beyond to your own data or organisation? Start a conversation.
CV
I am an independent data professional with a background in applied data science, machine learning, and telecommunications. I span expertise across public health, modern information technology, and business support.
Education
PhD in Telecommunications Research
King’s College London, UK
MSc in Telecommunications and Internet Technology
King’s College London, UK
BEng in Information Engineering
Wuhan University of Technology, China
Selected Experience
Research Fellow — Genome Research Limited (Wellcome Sanger Institute), Cambridge, UK
Machine-learning and Bayesian modelling for large-scale genomic surveillance, workflow automation, and population-level decision support.
Honorary Research Associate / Research Associate — Imperial College London, London, UK
Development of predictive models for genomic epidemiology, disease burden forecasting, and antimicrobial resistance, alongside supervision and teaching.
Visiting Scholar — Tampere University, Tampere, Finland
Research on reliable systems and coexistence frameworks for next-generation wireless networks.
Core Skills
- Applied machine learning & statistical modelling
- Bayesian inference & forecasting under uncertainty
- Large-scale data curation & workflow automation
- Python, R, SQL, MATLAB, Shell scripting
- Reproducible research & technical documentation
Languages
- English — professional
- Mandarin — native
- German — conversational
- Cantonese — conversational
- Russian — basic
Publications
Peer-reviewed publications in IEEE journals and conference proceedings, alongside ongoing work in genomic epidemiology and public-health modelling.
Access my publications sites from King’s · Imperial · Google Scholar · ORCID
Teaching & Public Engagement
Experience delivering postgraduate and undergraduate teaching, supervising PhD student projects, and engaging in public and interdisciplinary research communication.
A full academic CV is available here.