TensorFlow
Used it to build deep neural networks and accelerate model performance using TensorFlow-GPU and CUDA
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Mercy Wangui Muiruri
Machine Learning and Full Stack Development
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Machine Learning and Full Stack Development
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Bachelor of Science in Computer Science
Machine Learning and Data Science Specialization
Expected Graduation: June 2027
I am currently a sophomore studying Computer Science with a specialization focus on Machine Learning.
As an African woman in STEM, I am also passionate about bridging the gap to increase representation of minorities in tech.
Relevant Coursework: Artificial Intelligence, Data Structures and Algorithms, Data Engineering, Cloud Computing, Linear Algebra and Statistics
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Used it to build deep neural networks and accelerate model performance using TensorFlow-GPU and CUDA
Used it to develop convolutional neural networks and for optimization using 'Adam optimizer'
Used it for data loading and preprocessing with OpenCV and OS libraries
Used it for text vectorization during data preprocessing
Used it to run regression models such as: SVR, Random Forest, KNN and Gradient Boosting
Used it for graphical visualization of data in exploratory analysis
Used AWS S3 for storing user data and containerized service using Docker
Used it to manipulate relatonal database via AWS CLI allowing users to store and retrieve data
Used it to write back-end object-oriented algorithms
Used it for routing and API support
Used it to build responsive client-side web apps
Used it with React to add dynamic functionality to websites
Used it to manipulate ML models and write code for ML libraries
Used it to graph ERGM and ALAAM data models
Timeline of my Experience
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.
Designed, developed, and maintained a fully functional and dynamic website ensuring optimal performance, user-friendly navigation.
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.
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