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Sonya-728/README.md

Hi, I'm Yixuan Sun 👋

I am a Bachelor of Science student at the University of Melbourne, majoring in Mathematics and Statistics with a specialisation in Statistics and Stochastic Processes.

My interests include statistical modelling, simulation, optimisation, machine learning, and data-driven decision making.

I enjoy using mathematical and computational methods to solve problems involving uncertainty, ranking, optimisation, and statistical inference.

Research

Text-Guided Pairwise Preference Learning under Noisy Annotator Disagreement

Sole-author research project on preference learning and group decision making.

The project investigates how text-derived pairwise preferences can be combined with noisy and heterogeneous annotators using reliability-aware aggregation.

Main areas:

  • pairwise preference learning
  • text representation
  • annotator reliability
  • ranking and aggregation
  • robustness to noisy and adversarial annotations

Counterfactual Stress Calibration for Rare Positive Risk Control under Distribution Shift

Third-author research project submitted to ACML 2026.

My contributions include dataset collection, data visualisation, and writing and revising parts of the introduction.

Featured Projects

🧮 Applied Statistical Modelling in R

Statistical analysis project covering regression, ANOVA, hypothesis testing, non-parametric methods, effect sizes, assumption checking, and data visualisation.

Tools: R, tidyverse, ggplot2

View repository

🧩 Study Group Optimizer

Python optimisation project that generates and allocates valid study groups under multiple constraints.

Uses combinatorial search, constraint validation, scoring, lexicographic tie-breaking, and recursive backtracking.

Tools: Python

View repository

🤖 Robotic Vacuum Cleaner Simulation

Grid-based robotic vacuum simulation featuring directional sensors, obstacle-aware movement, dirt detection, cleaning cycles, and stack-based backtracking.

Tools: Python

View repository

🔬 Cellular Automata Simulation

One-dimensional cellular automata simulator implemented in C, including rule-based state evolution, linked data structures, and density classification.

Tools: C

View repository

Technical Skills

Programming: Python, R, C, MATLAB

Statistics: Regression, ANOVA, hypothesis testing, non-parametric methods, statistical modelling

Algorithms: Simulation, combinatorial search, optimisation, backtracking, pairwise ranking

Tools: RStudio, tidyverse, ggplot2, Git, GitHub, LaTeX

Education

University of Melbourne
Bachelor of Science
Major: Mathematics and Statistics
Specialisation: Statistics / Stochastic Processes
Expected graduation: December 2026

Current Interests

I am particularly interested in postgraduate study and research involving:

  • statistical modelling
  • modelling and simulation
  • optimisation
  • machine learning
  • data science
  • stochastic processes

Contact

📧 sunny200429@gmail.com

Pinned Loading

  1. cellular-automata-simulation cellular-automata-simulation Public

    One-dimensional cellular automata simulator implemented in C, including rule-based state evolution and density classification.

    C

  2. robotic-vacuum-simulation robotic-vacuum-simulation Public

    Grid-based robotic vacuum cleaner simulation implemented in Python with sensor-based dirt detection and backtracking.

    Python

  3. applied-statistical-modelling applied-statistical-modelling Public

    Statistical modelling and hypothesis testing in R, including ANOVA, regression, non-parametric tests, and effect-size analysis.

    R

  4. study-group-optimizer study-group-optimizer Public

    Python study group optimiser using combinatorial search, constraint validation, scoring, and recursive backtracking.

    Python