About
Machine Learning Engineer with a strong mathematical background, experienced in building end-to-end ML systems in PyTorch. Worked on research-driven generative models for structured and relational data, including sequence- and network-based representations, covering data processing, model design, training, and evaluation.
Work Experience
M&C Saatchi World ServicesPythonTypeScriptFastAPINetworkXPyvis
Data Intern
- ⦿ Developed a time-series network visualization and prediction tool using state-of-the-art DAMNETS model, enabling stakeholders to identify emerging influence patterns and forecast network evolution across social media data.
- ⦿ Presented findings to non-technical stakeholders across multiple teams, driving adoption of network analysis for client account strategy.
- ⦿ Top-performing intern; recommended for return offer by management and data science team.
Thesis
- ⦿ A. Tuna, "A Deep Autoregressive Model for Dynamic Combinatorial Complexes," arXiv preprint, 2026. DOI: 10.48550/arXiv.2503.01999.
Education
Imperial College London
University of Edinburgh
Projects & Awards
Developed a novel autoregressive generative model for structured, high-dimensional graph and combinatorial data (arXiv:2503.01999). Implemented the model in PyTorch with custom loss functions, evaluation pipelines, and memory-aware handling of sparse, high-dimensional structures.
Pabu
Co-designed and implemented a Chrome extension for AI-driven content filtering, selectively blocking distracting online material while allowing context-relevant resources. The project was developed collaboratively during the AI Engine Hackathon and awarded 3rd Place for Best Use of ACI.dev Unified MCP.
HYPED
Designed and oversaw manufacture of the monorail–pod structural interface, enabling stable operation at speeds up to 311 km/h, for the UK’s leading Hyperloop team; Uthe project was recognised by SpaceX, Virgin Hyperloop One, and the Institution of Civil Engineers, and reached SpaceX finals in Los Angeles.
ML Research & Modelling Skills
Languages
Leadership
University of Edinburgh, School of Mathematics
MathClans Leader
- ⦿ Fostered a sense of community by leading peer integration initiatives for new students.
- ⦿ Organised academic and social events supporting student engagement and departmental cohesion.
Edinburgh University Students' Association
Programme Representative, Academic Societies Representative
- ⦿ Gathered feedback and represented third-year Mathematics students in the Student-Staff Liaison Committee.
- ⦿ Liaised between academic societies and the Association, contributing to governance via motions and proposals.