Closing one chapter, opening another
After six years at Mastercard, I said goodbye to the team that shaped my early career and prepared to move to London for a master’s in Computer Science at Queen Mary University of London.
View original postQueen Mary University of London · 2025–2026
My masters journey
A year of moving from industry back into education: studying Advanced Computer Science, building with new communities, and making London part of the classroom.
13 milestones
1 academic year
London the wider campus
The timeline
Learning beyond lectures
Academic milestones sit alongside the fellowships, meetups and hackathons that shaped the year.
Starting the MSc at QMUL
I began the MSc in Advanced Computer Science, bringing six years of industry experience into deeper study of machine learning, big data and functional programming.
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Third place at my first London hackathon
Representing the QMUL Computer Science Society, our team built Phantom Fraud in 72 hours and placed third in the Encode London Hackathon’s Solana bounty.
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My first London tech meetup
I headed to London.js after classes and learned about web performance, creative programming education and emerging protocols for AI agents.
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Exploring the modern data stack
A Confluent workshop connected classroom interests with a live pipeline spanning Kafka, Flink, time-series forecasting, Iceberg and DuckDB.
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Making space to keep learning
Between university work and London life, I took The Scaling Era to the Thames and reflected on the people and ideas shaping modern AI.
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Returning to fintech with a student’s perspective
Finovate Europe offered a fresh look at financial services, AI and fraud defence while reconnecting my master’s studies with my earlier payments experience.
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Accepted into Nebius Academy
In the middle of exam season, I joined a 14-week AI Engineering fellowship to study LLM architecture, performance engineering, post-training and production MLOps.
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Building a code-aware repository summariser
For the Nebius Academy challenge, I built an API that uses Tree-sitter and token-budgeted context assembly to turn GitHub repositories into useful summaries.
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Designing for work at the lab bench
Our Interactive System Design project explored how wet-lab researchers document experiments, moving from user research and conceptual models to iterative prototypes.
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Seeing AI infrastructure at production scale
At Nebius Build/Lon, I connected the fellowship’s foundations to GPU-era serverless systems, inference performance, coding benchmarks and real-world agent reliability.
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Bridging deep science and venture capital
At the Tech Europe Hackathon, our team built an AI research-to-investment pipeline and received an award for the event’s most secure codebase.
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Ending the year among London’s builders
A Replit London conversation with Amjad Masad and Paul Graham made a fitting final marker for a year spent studying, building and joining the city’s technology community.
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