Open to opportunities

Yang Yu

@yangyu

Message

PhD-qualified data scientist specializing in machine learning and statistical modeling.

China

Message

What I'm looking for

I am looking for opportunities that allow me to leverage my data science skills in impactful projects, particularly in public health and environmental sustainability.

I am a PhD-qualified data scientist with a robust foundation in machine learning, statistical modeling, and mathematics. My expertise lies in transforming complex datasets into actionable insights, particularly in the realm of flood risk forecasting. I successfully delivered a 94% accurate prediction model that has been recognized by stakeholders as a baseline for future urban planning, showcasing my ability to address social challenges through data-driven solutions.

In my recent role as a Postdoctoral Research Associate at the University of Liverpool, I deployed a long COVID prediction model on interactive dashboards, significantly enhancing public health decision-making. My work has consistently focused on improving data processing efficiency, achieving a 67% reduction in processing time through parallel computing. I have also developed bespoke solutions for stakeholders, tailoring insights to inform local employment support strategies.

With a strong emphasis on Bayesian statistics and advanced statistical modeling, I have contributed to various projects that require innovative approaches to data analysis. My academic journey has equipped me with the skills to handle large-scale datasets and deliver impactful visualizations that drive strategic decisions.

Experience

Work history, roles, and key accomplishments

Current

Postdoctoral Research Associate

Current

University of Liverpool

Apr 2023 - Present (2 years 2 months)

Performed a multinomial logistic regression model and a multivariate correspondence analysis to identify key risk patterns in workless populations who accessed mental health services. Improved data processing speed by 55% through parallel computing.

Machine Learning Statistical Modelling Python R Parallel Computing

Postdoctoral Research Associate

Newcastle University

Nov 2021 - Present (3 years 7 months)

Designed and implemented an advanced statistical model to predict the age-distributed long COVID rate across local authorities. Visualised long COVID prediction on geographical charts and created an interactive real-time dashboard using R Shiny.

Statistical Modelling R Shiny Frailty States Data

Postdoctoral Research Associate

Newcastle University

Aug 2019 - Present (5 years 10 months)

Developed a Gaussian Process emulator to forecast maximal flood depths spatially with 92% forecast accuracy. Designed Markov Chain Monte Carlo (MCMC) algorithms to estimate the model from a Bayesian perspective.

Gaussian Process Dimension Reduction Flood Forecasting

PhD Researcher

Beihang University

Sep 2014 - Present (10 years 9 months)

Proposed a Bayesian nonparametric approach to perform local smoothing quantile regression, reducing estimate error by 26%. Developed Bayesian quantile regression and variable selection to estimate the partial linear single-index model.

Quantile Regression Nonparametric Bernstein Dirichlet Approximation

Education

Degrees, certifications, and relevant coursework

University of Auckland

Visiting Student in Statistics, Statistics

Focused on advanced statistical methods and their applications. Gained exposure to new research methodologies in the field of statistics.

Nanjing University of Finance and Economics

MSc in Probability and Mathematical Statistics, Probability and Mathematical Statistics

Presented Bayesian quantile regression and variable selection for hierarchical linear models, implementing estimation using MCMC. Developed Bayesian quantile regression to model the ordinal categorical outcomes in a classification framework.

Shandong Agricultural University

BSc in Information and Computing Science, Information and Computing Science

Studied the fundamentals of information and computing science. Gained foundational knowledge in various computational theories and practices.

Beihang University

PhD in Management Science and Engineering, Management Science and Engineering

Proposed a Bayesian nonparametric approach to perform local smoothing quantile regression, designing MCMC algorithms for estimation and reducing estimate error by 26%. Developed a nonparametric Bernstein-Dirichlet approximation to estimate the single-index model, with MCMC algorithms for estimation and a 20% reduction in estimate error. Developed Bayesian quantile regression and variable selection