Priestly Adejo
I build software and models for markets, machines and messy data.
UCL MEng, Upper Second-Class Honours (2:1) · SLB and Ura Thrusters · London
Seeking graduate and early-career roles in quantitative development, research engineering and trading systems.
Competition projects
Competition work lives in Projects. Filter the full list by Competition.
Model to Market
A solo-built systematic trading system for QuantHack’s Model to Market competition, spanning data ingestion, research, validation, portfolio risk, MT5 execution and live telemetry.
Onyx Future of Energy Trading Research
A competition research submission and post-event reconstruction of how the US–Iran conflict moved through Hormuz shipping risk, Gulf oil flows, product markets and energy-security policy.
Forecasting the Future 2026
A forecasting project on how AI investment, energy infrastructure and modern mercantilism could reshape markets and national power over the next decade.
Featured work
QuantSilico
A structured research and deployment system for systematic trading: one place to define ideas, test them properly, keep evidence, promote what survives and monitor what happens once it runs.
Live Data Monitoring Platform — Coastal Buoy
A first-generation coastal sensing platform combining underwater acoustics, motion, temperature and position with local raw-data capture and live cellular monitoring. UCL MEng final design project.
Target-Conditioned De Novo Molecule Generation for FGFR2
An individual computational study that adapted TargetVAE and TeachOpenCADD components to generate, filter and rank molecular structures for an FGFR2 case study in intrahepatic cholangiocarcinoma.
Latest writing
From Sensor Stream to Shore: Engineering a Store-and-Forward Coastal Buoy
How a UCL team turned an inherited passive buoy into a live coastal sensing platform, and why data integrity, power and validation mattered more than adding another sensor.
Model to Market, Part 3: Live Risk, Telemetry and What I Would Change
What the live telemetry recorded, how the configuration changed during the competition and what I would redesign after the final run.
Model to Market, Part 2: What Made It Live and What I Rejected
The tests, failed candidates and promotion decisions that determined which strategies could influence the competition account.
Skills snapshot
- Python
- C++
- MATLAB
- SQL
- Git
- Jupyter
- pytest
- GitHub Actions
- Docker
- structured logging
- modular package design
- reproducible pipelines
- configuration-driven systems
- market data ingestion
- vectorised and event-driven backtesting
- portfolio sizing
- transaction-cost modelling
- execution logic