I'm a high-school student in the computer science track in Bizerte, Tunisia, preparing the 2027 Tunisian Baccalaureate.

I co-founded Disuza Quantitative, an independent R&D initiative focused on financial data and systematic trading research. I work with Python, data pipelines and cloud infrastructure, with an interest in making experiments reproducible and their limitations clear.

Role: Co-founder — technical research and engineering
Research scope: Cryptoassets and index futures

The project has gone through several generations, including rule-based signals, machine-learning models and event-driven simulation.

Areas of work include:

• Market-data infrastructure: Multivenue collection, monitoring, archiving and recovery workflows.
• Data quality: Dataset preparation, structural checks and documentation of coverage and timing assumptions.
• Research and simulation: Exploratory analysis, backtesting, cost and risk controls, and reproducible evaluation.
• Engineering: Cloud workflows, automated checks and documentation of results, unsuccessful experiments and remaining limitations.

Current stage: Research and development. Data collection and monitoring are operational components. The newer engine has a bounded qualification on synthetic scenarios; economic validation of a trading strategy remains an open research objective.

Public technical documentation — architecture, methodology and dated project-status statements. The core research and execution source code remains private.

I use AI-assisted workflows for software development and research support, alongside testing, documentation and review. I distinguish observed results, current limitations and future objectives.

Domain	Stack
Core
Data Engineering
Quantitative
Environment

I plan to study computer science or artificial intelligence at university. I'm also exploring computational biology and longevity research as areas I want to learn more about.