Realtor.com
Machine Learning Consultant
During my time at Emory University, I had an opportunity to work on industry business projects, addressing real business challenges. I was privileged to join a team collaborating with Realtor.com to enhance their autocomplete feature, aiming to personalize it further for users on their platform to increase engagement. This project is still underway.
The technical stack we are using include: Python, SQL, and cloud services (AWS). We are leveraging the above tools to
improve the user experience on
Realtor.com.
AWESOMITY LAB
Machine Learning Lead
I have always been intrigued by the potential of cutting-edge AI technologies. After earning my Master's degree from Carnegie Mellon University, I had the opportunity to join
Awesomity Lab as a Machine Learning Lead,
a company renowned for its exceptional software services in Rwanda.
During my time there, I was fortunate enough to lead a project focused on implementing a computer vision algorithm.
Our goal was to predict the weight of lambs using 3D imagery. Impressively, we achieved a prediction error rate of just 5%, which significantly reduced the operational costs for our client's livestock management.
The project served as a pivotal prototype, showcasing how AI can revolutionize the farming industry.
It was not just about the technological achievement but also about demonstrating AI's capacity to enhance efficiency and sustainability in agriculture,
setting a precedent for future innovations.
JP Morgan
AI Researcher
During my time at
Carnegie Mellon University in September 2022, I had the opportunity to work on a project involving low-resource languages spoken in Central Africa,
which are crucial for the development of Conversational AI. At that time, it was challenging to find Large Language Models capable of interacting with these lesser-known languages.
Existing solutions, including those from leading companies like Google, were not good, highlighting the need for extensive research to advance the field and contribute to the community.
My teammates from CMU, along with a group of researchers from
JP Morgan, focused on the preliminary task of Natural Language Understanding. This task is a cornerstone of Conversational AI, involving the prediction of a user's query intent and its corresponding slots.
In our study, we managed to compile a dataset for the community that includes human translations for three languages: Swahili, Kinyarwanda, and Luganda. We conducted baseline experiments using pre-trained language models, including mBERT and XLM-Roberta, which showed promising results. We shared our findings and methodologies in
a paper presented at a conference, aiming to inspire further research within the community.
Carnegie Mellon University
Research Associate
After my graduation from CMU, I continued working with Professor
Barry Rawn on a project for the Rwanda Energy Group, primarily focusing on analyzing data silos within the company.
The project was exciting because it allowed me to learn how to create interesting visualizations using new JavaScript frameworks such as D3.js, as well as Python, to clearly demonstrate complex data insights.