I recently graduated with a First-Class BSc Hons. in Artificial Intelligence and Computer Science degree at the University of Edinburgh after successfully publishing my first undergraduate thesis. I currently intern as a Business Intelligence Engineer at Amazon EU Sarl in London.
Published my undergraduate thesis (achieving 77%) and completed my BSc Hons degree.
Working as a Business Intelligence Engineer intern in the Supply Chain Execution Department at the London office.
Developed a search engine, a real-time human activity recognition app, an assistive robot, and much more!
Due to school policies, all university coursework sourcecode repositories must remain private
Detecting Long-Term Deviation and External Factors Correlations in Activities of Daily Living Based on Sensor Data, supervised by Dr Jacques Fleuriot. Using machine learning and deep learning techniques for human activity recognition over years of sensor data (82% overall accuracy), clustering, process mining, and activity forecasting.
Python, TensorFlow, Scikit-Learn, PM4Py, Prophet, NeuralProphet, Git
In a team of six, we developed a full-stack web search engine for 10m Spotify podcast transcript snippets, enabling the user to listen to only the parts of podcasts they are interested in. Features include ranked information retrieval, semantic search, topic modelling, query expansion, and CI/CD using Jenkins via GitHub.
Python, Flask, React, PostgreSQL, MongoDB, Docker, Google Cloud, Jenkins, Git
We developed a full-stack mobile app for real-time human activity recognition from wearable sensors in a team of three. We used deep learning to achieve classification accuracies of 94% for 4 activity subsets and 72% for 14 different activities. The app shows the classified activity, step count, and stores historical user data using Firebase.
Python, TensorFlow, Keras, Scikit-Learn, Java, Kotlin, Firebase, Git
I am a member of AIML, the Artificial Intelligence Modelling Lab research group at the University of Edinburgh's AIAI institute (Artificial Intelligence Applications Institute). I held two talks about my dissertation's research goals, proposed methods, and concluded findings as part of my viva preparations. I also regularly attended other research talks, learning about state-of-the-art machine learning applications.
