Terraform
Migrated testing infrastructure at Oracle by building 120+ Terraform modules
Hello, thanks for stopping by!
Mercy Wangui Muiruri
Hello, thanks for stopping by!
Get To Know More
Bachelor of Science in Computer Science
Machine Learning and Data Science Minor
Expected Graduation: June 2027
I am currently a junior studying Computer Science with a focus on infrastructure and full-stack development.
As an African woman in STEM, I am also passionate about bridging the gap to increase representation of minorities in tech.
Relevant Coursework: Machine Learning, Networking, Artificial Intelligence, Data Structures and Algorithms, Data Engineering, Cloud Computing, Linear Algebra and Statistics
Migrated testing infrastructure at Oracle by building 120+ Terraform modules
Deployed 40 Java artifacts into Kubernetes clusters using blue-green deployment strategies
Packaged and standardized my Java code into isolated artifacts for deployment
Integrated backend services into production using CI/CD tools like Shepherd to deploy artifacts
Architected and built backend APIs for Oracle databases in Java using industry frameworks like DropWizard, Maven, Swagger API, Guice etc
Executed backend APIs and requests against Oracle's databases: SQL, Exadata and Virtual Machines
Designed and developed multiple user interfaces using React and React frameworks like React Native for mobile applications
Leveraged object-oriented Python programming to build mathematic graphical Pythonic UIs using Python libraries like: matplotlib, streamlit
Developed middleware servers using JavaScript to receive user requests and route to the database for processing
Enhanced code reliability and developer productivity through static typing and advanced object-oriented patterns
Crafted responsive, mobile-first web designs with modern CSS techniques and cross-browser compatibility
Harnessed node.js single-threaded quality to build web servers to process REST APIs
Built robust backend services and RESTful API endpoints with middleware authentication and database integration
Built and deployed full-stack applications with real-time databases, serverless functions, and integrated authentication using modern BaaS platforms
Timeline of my Experience
Developed backend services and infrastructure usign Java and Terraform in the multi-cloud organization (Oracle x Google Cloud platform) in Oracle.
Selected as 1 of 47 out of 2500+ applicants to work with senior Netflix engineers on system design and technical aspects in data structures and algorithms, system design and object-oriented programming
Engaged in Amazon’s Campus Prep Series, a technical program covering data structures, algorithms, and behavioral interview preparation through mock interviews, engineer Q&As and role shadowing
Worked in Square One, a startup focused on promoting children's health and building a application to guide children on healthy habits/practices
Participated in a selective, invite-only professional development Summit focused on technical and career growth in tech.
Optimized a course recommendation model for 477 schools processing datasets with 10,000+ school records to build an automated ETL data pipeline (Pandas + NumPy + SciPy) to provide course recommendations.
Won the Northwestern IEEE 2025 competition in a team of 6 by building an end-to-end web application integrated with NoSQL Supabase, React + Bootstrap frontend with Node.js APIs for a volunteer recommendation service.
Currently working with a team of faculty and 15 undergrads to supervise, grade and tutor 170 CS students at Northwestern University on core Data Structures and Algorithms. Hold weekly office hours to handle code reviews, debugging assistance and break down problems in order to find resolution.
Assist event organizers with AV needs and troubleshoot and resolve technical issues in case of any. Set up and perform regular maintenance checks on audio-visual equipment such as projectors and sound systems.
Browse My Recent
Developed a multi-headed comment toxicity detection model used to filter against online abuse. Achieved a 97% accuracy using a TensorFlow Keras Sequential architecture (Embedding, Dense layers, Sigmoid activation). Deployed an interactive Gradio web UI for real-time comment classification.
Built a convolutional deep neural network for audio classification, where the model can recognize specific sound from a recording. Preprocessed and segmented large audio files with TensorFlow_IO, converting sound to a spectogram of waveforms which was later vectorized to tokens for parsing and training the model.
Architected a deep learning model to predict crop yields from weather and farming data like rainfall and soil quality. Leveraged Pandas for data cleaningcorrelation analysis and Seaborn for visualization. Explored SVR, KNN regression, and built a Sequential neural network for final predictions.
Developed a cloud-based photos app using AWS S3 and AWS RDS (MySQL/SQLite), allowing users to store large files like images and retrieve data. Integrated AWS Rekognition AI to enable the model to tag and label images inorder to implement search functionality. Application was containerized using Docker to allow for multi-platform support.
Developed a responsive React web application using JavaScript and Tailwind.
Currently working with 4 students to build a Python-based interface for Northwestern’s Formula Racing club to visualize sensor data in real time and aid in data analysis and interpretation. Intended to be used during car testing to pinpoint and fix design flaws. We are currently using customTkinter libraries for a responsive UX and Matplotlib for dynamic/static graphing.
Collaborated in a team of 20 students to graph real-time suspension simulations for our racecar's engine in C and C++. Improved data transmission efficiency by utilising CAN Bus for communication and intergrated functional unit tests. Prototyped PCB designs with CAD and Eagle for our circuits and
Conducted data analysis on a Reddit dataset in order to inform marketing strategies for an online gaming company, identifying the most influential subreddits via Eigenvector measures. Utilised social network statistical models like ALAAM to analyze network ties REM(Relational Event Models) to predict clustering and ERGM to predict patterns of ties in the network.
Developed a trip planner application to allow users to locate areas of interest when travelling to unknown areas and use current location to find nearby utilities like restaurants. Leveraged the low-level functional nature of DSSL2 (a Lisp language) to build necessary data structures like stacks and queues from scratch and implement fundamental traversal algorithms.
Developed a Python interpreter in C using tokens that translated Python code to lower level code.
Designed and built the famous snake game using functional Racket language.
Deciphered a fictional attack "bomb" to train on cybersecurity using low-level assembly code. Utilised GDB and GNU debugger to fix bug issues in assembly code in order to solve the "bomb". Worked with Linux and Unix to write a CLI commands to manipulate operating system.
Relevant Organizations
Get in Touch
