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Technology skills

Programming
Python · R · MATLAB · SQL (T-SQL)
Python libraries
pandas · NumPy · SciPy · scikit-learn · matplotlib
Statistical & predictive modelling
Bayesian inference · Classification · Logistic regression · Gradient boosting · Machine learning
Analysis & validation
Scenario analysis · Model validation · Parameter estimation · Uncertainty analysis · Data visualisation
Tools
Power BI · Excel · Git · GitHub

Interpersonal skills

Professional strengths
Technical communication · Workshop facilitation · Collaboration · Problem solving · Attention to detail

Main

Ati Rostami

Research Data Scientist with a PhD in applied mathematics, specialising in mathematical modelling, simulation and Bayesian inference. Experienced in analysing plant growth models, building machine learning models in Python, and communicating findings through research and teaching.

Professional Experience

AI Resident

Apziva

Remote

Present - 2026

  • Built predictive models in Python to analyse customer satisfaction and identify customers likely to subscribe to a term deposit.
  • Compared logistic regression, support vector machines, random forests and gradient boosting using scikit-learn to evaluate predictive performance.
  • Achieved an F1 score of approximately 0.71 for term-deposit subscription prediction using gradient boosting.

Research Data Scientist

Plant Success Centre

Brisbane, Australia

2026 - 2021

  • Developed and analysed whole-plant carbon-nitrogen models using numerical simulation to investigate shoot and root growth.
  • Conducted scenario analysis and parameter sweeps to identify unrealistic model behaviour; improved the model structure by adding litter terms.
  • Applied Bayesian sequential Monte Carlo to synthetic dry-mass data for parameter estimation, uncertainty analysis and assessment of parameter correlations.
  • Used principal component analysis of posterior samples to assess parameter identifiability and determine which parameter combinations were informative.
  • Compared measurement scenarios to understand data limitations, draw insights and provide recommendations for experimental design; communicated findings to interdisciplinary researchers.

Teaching

Teaching Associate (Mathematics, Programming & Data Science)

Queensland University of Technology

Brisbane, Australia

Present - 2023

  • Delivered workshops, practical labs and tutorials in mathematics, data science and programming to hundreds of undergraduate students across multiple units.
  • Taught R in Advanced Visualisation and Data Science, supporting data analysis, visualisation and lab portfolios; also taught MATLAB, calculus, statistics and algebra, and assessed coursework.

Education

PhD, Applied Mathematics

Queensland University of Technology

Brisbane, Australia

2026

  • Thesis: Re-engineering Enduring Mathematical Models Using Novel Techniques and New Data

MPhil, Pure Mathematics

K. N. Toosi University of Technology

Tehran, Iran

2015

  • Thesis: Hyperconvex Metric Spaces

BSc, Pure Mathematics

Shahrood University of Technology

Shahrood, Iran

2011