Ryan Teo
I am a current MSc student at the MathSys CDT. My research interests include infectious disease modelling, statistical learning, and spatial statistics. In particular, I am keen on applying mathematical modelling to improve pandemic preparedness and outbreak response.
Projects
Modelling a Global Outbreak of a hypothetical human-transmissible Highly Pathogenic Avian Influenza H5N1
Stanford Existential Risks InitiativeLink opens in a new window Summer Research Fellowship (2021)
- Supervisor: Dr Robin ThompsonLink opens in a new window
- Highly Pathogenic Avian Influenza (HPAI) H5N1 is a strain of influenza that is lethal to but not efficiently transmissible between humans, with the case fatality rate estimated to be around 58%. It has also been the subject of controversial "gain-of-function" experiments which could potentially lead to it becoming efficiently transmissible between humans
- Developed a global meta-population SEIR epidemic model with location-specific contact and travel rates to model the global impact of an outbreak of a hypothetical human-transmissible HPAI H5N1
- Quantified the probability of a pandemic of HPAI H5N1 occurring and its expected final size and death toll under various policy scenarios
Predicting population susceptibility to dengue over space and time in Singapore
Honours Project in Statistics (2020 - 2021)
- Supervisors: Dr Hannah ClaphamLink opens in a new window and Dr Alex CookLink opens in a new window
- Estimated the time-varying force of infection of dengue from serological data and derived the age-specific seroprevalence of dengue in different locations and at different time points
- Utilised methods in spatial statistics including Kriging and Area Weighted Interpolation to analyse and visualise spatial data
- Conducted parameter inference with Hamiltonian Monte Carlo in Stan
- Received the Lijen Industrial Development Medal for the best honours project in the discipline and Regional Winner prize for the 2021 Global Undergraduate AwardsLink opens in a new window for the highest-performing entry from Asia in the Mathematics & Physics category
Projecting Healthcare Utilisation by Low-Income Elderly in Singapore using a Dynamic Multi-State Population Model
Project in Systems Thinking and System Dynamics (2018 - 2020)
- Supervisor: Dr John AnsahLink opens in a new window
- Developed a Markov state model that segmented the low-income elderly population in Singapore into health states with differing Health and Social Services needs and complication levels
- Projected the changing distribution of elderly in these health states from 2010 to 2040 and assessed its impact on healthcare service utilisation
- Presented findings at the 3rd Asia Pacific Systems Dynamics ConferenceLink opens in a new window organised by the University of Queensland in Brisbane, Australia
Monitoring PM2.5 Concentrations near the Tibetan Plateau
Zhejiang University Summer Research Programme (2019)
- Supervisor: Dr Zhang FengLink opens in a new window
- Implemented Geographically and Temporally Weighted Regression to estimate and predict PM2.5 Concentrations near the Tibetan Plateau from MODIS Aerosol Optical Depth remote sensing data
Education
Bachelor of Science (Honours) in Statistics (Highest Distinction)
National University of Singapore (2017 - 2021)
- Specialisation in Data Science with minors in Public Health and Geographical Information Systems
- Recipient of the NUS Merit Scholarship
