Hi, I'm

Mohamed
ElDebawy

Currently studying for an MSc in Artificial Intelligence at the University of Bristol. I'm passionate about quantitative finance and AI, and I build systems that learn from data, including an automated trading strategy that beat its market benchmark 2.85×.

View my work → Get in touch
Mohamed ElDebawy at his University of Bristol graduation
🎓 MSc AI · Bristol
📈 Co-founder, Quant
0%
Strategy return over ~10 months
0×
The EGX30 market benchmark
0%
Precision of my orange-detection model
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Master's degrees: Engineering, AI, Financial Eng.
About me

Passionate about
quant & AI.

I'm currently doing a Master's in Artificial Intelligence at the University of Bristol. My interests lie in quantitative finance and AI, and especially where the two meet: using machine learning to find signals in markets.

Before that, I graduated from the University of Bristol with an MEng in Electrical & Electronic Engineering, including a year at Intel R&D working on FPGA cloud network accelerators.

Since 2024 I've co-founded a systematic trading project in Cairo, where I research signals, build predictive models and run them through an automated pipeline. I'm also studying a Master's in Financial Engineering at WorldQuant University.

I like hard problems, whether that's a noisy market, a stuck ball in a maze or a scrambled Rubik's cube. I also won the Intel PSG UK chess tournament.

Languages

PythonRSQLCVHDLVerilogMATLAB

AI & data

PyTorchNumPyBoostingRandom ForestYOLOOpenCV

Quant

BacktestingTime seriesRegime detectionDerivative pricing

Hardware & tools

FPGARaspberry PiSimulinkModelSimAWSLinuxGit
What I do

Three fields, one mindset

Click a field to see the projects behind it.

Quantitative Finance

Finding signals in market data, building models around them, and testing them properly before trusting them with money.

See quant work →

AI & Machine Learning

Deep learning, computer vision and algorithms, from detecting fruit in real time to studying why neural networks overfit.

See AI work →

Electronics & Embedded

FPGA and chip design, signal processing, robotics and electric motor design. This is where I learned to build things that work.

See engineering work →
Selected work

Projects

A short overview of each one. Click a card for highlights, videos and visuals.

Currently

Ongoing projects

What I'm working on right now.

In progress

Scaling the trading system

Building regime-aware models that adapt to bull and bear markets, and exploring reinforcement learning and game theory so the strategy can scale to fund-sized capital.

In progress

MSc AI coursework, Bristol

Underfitting & overfitting in neural networks

How network size, early stopping and weight decay affect underfitting and overfitting, plus an independent investigation of my own.

Large-scale data engineering on AWS

Designing a secure, scalable cloud architecture for an AI photo-to-recipe app, and adding auto-scaling to a distributed data-processing app (EC2, S3, SQS, DynamoDB).

In progress

MSc Financial Engineering

WorldQuant University, part-time: econometrics, derivative pricing, stochastic modelling, and alternative data such as news and satellite data.

Journey

Education & experience

Tap any step for more.

Education
Sep 2026 – Present

MSc Artificial Intelligence

University of Bristol

Modules include Statistical Computing, Foundations of AI, Large-Scale Data Engineering, Advanced Deep Learning & Computer Vision, and the Theory and Practice of Large Language Models.

Experience
Sep 2024 – Present

Quantitative Analyst & Co-Founder

Systematic trading project · Cairo, Egypt

Researching signals in the Egyptian stock market, building machine-learning models, and running them through an automated daily trading pipeline. 166.77% return in paper trading vs 58.19% for the EGX30 over the same period.

Education
Sep 2024 – Present

Master's in Financial Engineering

WorldQuant University · part-time online

Financial and alternative data, econometrics and time series, regime switching, and derivative pricing from Black-Scholes to reinforcement learning.

Experience
Jul 2021 – Aug 2022

Smart NIC (RTL FPGA) Engineer Intern

Intel R&D · Marlow, UK

Debugged and optimised network performance on an FPGA cloud network accelerator, and brought up an ARM Cortex-A53 processor on an Intel Agilex FPGA.

Education
2019 – 2024

MEng Electrical & Electronic Engineering

University of Bristol · with a Year in Industry · Upper Second Class (68%)

Specialised in DSP & FPGA implementation, digital design, electric propulsion and power electronics. Research project on AI-powered orange harvesting.

Beyond the work

A little more about me

🎤

Speaker at AUC FINCON

Gave a talk to students on quantitative investing and its future in emerging markets.

♟️

Chess champion

Won the Intel PSG UK chess tournament without losing a round. Former Bristol Chess Society member.

🔬

STEM Ambassador

Ran engineering workshops for children to inspire the next generation of engineers.

📐

Maths teaching assistant

Ran A-level drop-in sessions and marked exam papers, finding new ways to explain hard problems.

Contact

Let's work together

I'm open to roles in quantitative research, AI/ML engineering and data-driven engineering. The best way to reach me is by email or LinkedIn.

✉ Email me in LinkedIn
bs19616@alumni.bristol.ac.uk Copied ✓
📍 Bristol, United Kingdom