I am interested in Cloud Computing and Distributed Systems, Systems Engineering, Site Reliability Engineering, and Research
in those areas. Previously worked in DevOps to drive engineering automation, teaching of Cloud Computing concepts, research
on Federated Learning, and technical leadership.
Experience
Graduate Teaching Assistant, Cloud Computing Course
Created and graded Docker and Kubernetes project assignments, improving student understanding and meeting learning objectives.
Assisted students in meeting course learning goals by explaining concepts and assignment requirements through Office Hours
and Piazza engagements. Facilitated enhanced learning in Docker and Kubernetes projects, as students reported exceeding
their initial expectations.
Research Assistant, Mobile Edge Lab
Conducted experiments to improve client-server communication in constrained environments, enhancing the accuracy of training
models through Federated Learning. Analyzed Federated Learning frameworks like Flower and research papers, using data from
testbed experiments with Kubernetes and RaspberryPI to identify innovative solutions. Authored a research paper discussing
innovative solutions for Federated Learning in constrained environments.
DevOps Engineer
Facilitated smooth CI/CD for a 20-member software development team collaborating on shared Linux VM instances.
Optimised cloud infrastructure, reducing GCP costs by 30% through the use of automation scripts in a virtualized
environment running on Kubernetes. Shortened delivery cycle from two weeks to four days by streamlining deployment
processes and incorporating performance tuning techniques.
Technical Lead
Led and managed a 5-member technical team on the website project, focusing on system configuration and cloud product
deployment, resulting in improved project delivery timelines. Guided developers in meeting client requirements and
enhancing system efficiency through targeted performance tuning. Oversaw project deployment and completion while
ensuring robust operational systems and streamlined processes.
Education
Master of Science, Information Technology
Focused on cloud computing, distributed systems, and systems engineering. Completed coursework in advanced topics
including Kubernetes, Docker, federated learning, and system optimization.
Bachelor of Science, Software Engineering
Comprehensive software engineering program covering software development methodologies, system design,
and computer science fundamentals.
Selected Projects
Utility-Optimizing Kubernetes Scheduler Extender
Designed and implemented custom scheduling policies for Kubernetes, optimising job utility and resource allocation.
Integrated the scheduler into Kubernetes, achieving target performance on realistic job traces through optimisation techniques.
Technologies: GoLang, Kubernetes Scheduler API, Kubelet
Plaid Shell
A custom Unix command line shell with support for interactive command parsing, built-in commands, globbing, and command history.
Developed and tested on Linux, utilising fork(), execvp(), and waitpid() for command execution.
Technologies: C, Test-Driven Development (TDD)
Federated Learning Research
Research on improving client-server communication in constrained environments for Federated Learning.
Utilized Kubernetes, RaspberryPI testbeds, and Flower framework for experiments and analysis.
Technologies: Python, Kubernetes, Flower, TensorFlow
Skills
Programming Languages: C, Python, Java, JavaScript, Ansible, Bash Shell, GoLang, Terraform
Frameworks: Git, GitHub Actions, Pandas, Scikit-learn, Node.js, OpenMP, CUDA, TensorFlow, FlowerFL, Apache Spark, Scrum
Tools & Infrastructure: Docker, Kubernetes, Prometheus, Grafana, ArgoCD, GitOps, Cilium, AWS, GCP, Azure, Openstack, Linux system administration
Frameworks: Git, GitHub Actions, Pandas, Scikit-learn, Node.js, OpenMP, CUDA, TensorFlow, FlowerFL, Apache Spark, Scrum
Tools & Infrastructure: Docker, Kubernetes, Prometheus, Grafana, ArgoCD, GitOps, Cilium, AWS, GCP, Azure, Openstack, Linux system administration