Evripides Georgiades

Computational researcher with expertise in quantitative data analysis, and mathematical and statistical modelling. Skilled in Python-based workflows for large-scale data analysis and computational tool development. Experienced with machine learning for practical problem solving. Comfortable with working on complex open-ended projects and collaborating with technical and non-technical teams.

Research Associate, Mechanical Engineering - Imperial College London

(2025-07)

• Developed Python-based numerical models, handling 200M+ data points and incorporating material variability statistics to analyse material properties and assess safety-critical component performance.
• Applied gradient-based optimisation to fit models to experimental and simulated datasets, extracting key parameters and validating assumptions.
• Delivered Machine Learning tutorial for over a three-year period, supporting over 200 students in practical and theoretical understanding.
• Collaborated with interdisciplinary teams, including experts from Penn State University and the University of Sussex, to interpret and integrate modelling results into broader research projects.

Consultant - Imperial Consultants

(2025-01)

• Led technical projects for major engineering organisations, including SSE and Scottish Power, managing deliverables and coordinating multidisciplinary engineering teams.
• Assessed state-of-the-art technologies and authored reports providing actionable recommendations for industrial partners, informing business decision-making.
• Briefed 20+ non-technical stakeholders with regular updates and summaries.

Research Associate, Mathematics - Imperial College London

(2025-01 - 2025-06)

• Built modular Python software to perform parametric simulations of sound transmission in batteries.
• Engineered data processing and visualisation tools to interpret simulation outputs and generate insights for design decisions.

Summer Intern — Audit & Financial Advisory - KPMG and Deloitte

(2017-06 - 2017-08)

• Supported audit and financial advisory teams by analysing financial records and verifying reporting accuracy.
• Shadowed professionals in financial services, gaining practical understanding of regulatory rules.

PhD - Mechanical Engineering - Imperial College London (2021-01 - 2025-01)

MSc - Pure Mathematics - Imperial College London (2018-10 - 2019-09)

BSc - Mathematics - University College London (2015-09 - 2018-06)