- Leading the transition of an Ad generation service with 1M unique daily users and 20M daily requests to an event-based architecture using Kafka, Java and Groovy- Increased online Ad revenue by 17% through designing and implementing an enhanced Ad filter showing sponsored products based on user’s chosen delivery date- Mitigated performance issues in service production pods running on a Kubernetes cluster by analysing memory usage patterns and tuning the garbage… Show more - Leading the transition of an Ad generation service with 1M unique daily users and 20M daily requests to an event-based architecture using Kafka, Java and Groovy- Increased online Ad revenue by 17% through designing and implementing an enhanced Ad filter showing sponsored products based on user’s chosen delivery date- Mitigated performance issues in service production pods running on a Kubernetes cluster by analysing memory usage patterns and tuning the garbage collector- Interviewed graduate engineers Show less

- Led design and development of a high-priority microservice that continuously synchronises concurrent changes of 7000+ clients - Refactored how product fees are calculated resulting in a simplified interface, removal of code and reduced complexity across 3 codebases- Investigated industry-standard monitoring solutions and wrote a set of guidelines internally used to set up monitoring and logging for over 30+ microservices- Mentored 2 engineers on coding practices and… Show more - Led design and development of a high-priority microservice that continuously synchronises concurrent changes of 7000+ clients - Refactored how product fees are calculated resulting in a simplified interface, removal of code and reduced complexity across 3 codebases- Investigated industry-standard monitoring solutions and wrote a set of guidelines internally used to set up monitoring and logging for over 30+ microservices- Mentored 2 engineers on coding practices and design principles- Interviewed junior and mid-level engineers Show less

- Researched compiler-based garbage collection optimisations targeted at big data frameworks like Spark and Hadoop- Discovered a parallel pattern-based approach that improved execution time by 1.3x and reduced memory usage by 2x for benchmarks resembling real-life big data applications- Published an open-source Hotspot JVM extension that enables manual memory management in Java- Mentored undergraduates on basic programming principles and OOP design

- Extended the frontend of a high-performance compiler by implementing the translation of basic language primitives such as enums and switch statements- Developed benchmarks that helped to evaluate and improve the introduced transformations

- Developed an AWS Lambda authoriser to support both public and private API calls in AWS ecosystem- Improved platform engagement by designing and implementing a service to handle user event tracking and notification delivery- Utilised AWS Personalize ML models to provide users with suggestions based on their platform usage history- Introduced gamification features to the platform which enabled users to progress and receive awards

- Developed an interactive web-based learning resource - ViLO (Visual Interactive Resource for Reinforcing Learning)- Implemented a prototype content management system that allowed lecturers to edit and maintain the resource content - Conducted interviews with students to understand how their learning could be enhanced- Published a paper in NDTPS 2018 titled "A Visual Interactive Resource for Supporting Self-Guided Learning"

- Developed a serverless data processing pipeline in AWS using Python, AWS Lambda and MongoDB to process 10000+ job vacancies daily- Introduced a custom AWS Lambda authoriser to support both public and private API calls in AWS ecosystem

- Improved a messaging simulator used for testing and reduced delivery time by helping product owners to perform E2E tests more efficiently - Reduced development cycle by parallelising integration tests