Geredi Niyibigira

Geredi Niyibigira

Geredi Niyibigira

Geredi Niyibigira

Machine Learning, Data Analyst and AI Engineer | LLM | Computer vision

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About Me

Contact Information

Languages

English 95%
French 40%
Swahili 30%

Professional Summary

Results-driven Machine Learning Engineer and Data Analyst with expertise in predictive modeling, Python development, and cloud-based data solutions. Combines strong technical foundations in SQL, Power BI, and data visualization with practical experience implementing end-to-end ML pipelines and automated reporting systems.

Demonstrated success in extracting actionable insights from diverse, high-volume datasets to drive measurable social impact, particularly within Monitoring & Evaluation frameworks. Experienced in healthcare applications, cloud infrastructure deployment, and cross-functional collaboration.

Committed to continuous learning, data quality excellence, and creating inclusive AI technologies that address real-world challenges in African contexts.

Education

Carnegie Mellon University, Africa

MSc in Engineering Artificial Intelligence

2023 – 2025

  • • Focus: Machine Learning, Large Language Models, Data Analytics, AI for Development, Cloud Systems, Deep Learning
  • • Relevant Coursework: Cloud Computing (15-319/15-619), AIOPs(04800-K), Introduction to deeplearning(11785), Data, Inference and Applied Machine Learning(18-785)
  • • Eng. AI Capstone (Final Project): A Conversational Notebook Assistant for AI/ML Workflows

University of Rwanda

BSc in Electronics and Telecommunication Engineering

2017 – 2022

  • • Final Project: Packet Delay Analysis in Heterogeneous Network using MATLAB and DTMC modeling

Professional Experience

Graduate Teaching Assistant

Carnegie Mellon University

2024 – 2025

  • • Assisting with the 11-785/485 Introduction to Deep Learning course, conducting recitations, designing quizzes, grading assignments, and mentoring students in Course Project.
TAs page

Artificial Intelligence Instructor

Glob Nexus Institute

2024 – 2025

  • • Guiding students in data science, machine learning, and AI, fostering a dynamic learning community for future tech innovators.
Learn more

Data Science Lab Apprentice

WorldQuant University

Apr 2023 – Jul 2023

  • • Completed 6 comprehensive data science projects focused on predictive modeling, data mining, and statistical analysis
  • • Built robust data pipelines for extracting, cleaning, and visualizing data from SQL, MongoDB, and APIs
  • • Conducted validation, metric definition, and automated reporting using Jupyter + Power BI
  • • Implemented cloud-based data storage solutions for efficient data processing

Single Line Generation Engineer

Might Engineering

Mar 2023 – Jun 2023

  • • Created single-line diagrams for solar PV systems using CAD tools, ensuring compliance with rigorous safety standards and regulatory requirements.

Key Projects

Featured Project

JupyterBuddy: Conversational Assistant for ML Workflow

Capstone Project | Carnegie Mellon University Africa | 2025

  • • Co-developed JupyterBuddy, an LLM-powered assistant for streamlining AI/ML workflows in JupyterLab using natural language commands and real-time code execution
  • • Designed a modular architecture with a React-based frontend, FastAPI backend, and LangGraph-based agent orchestrating tool invocations, achieving 100% tool call accuracy and 36% latency reduction
  • • Integrated retrieval-augmented generation (RAG) with FAISS and Sentence-BERT to provide context-aware, document-grounded responses for tasks like EDA, model training, and debugging
  • • Enabled dynamic interaction with notebook cells (create, edit, execute, delete), real-time feedback, and error resolution for seamless AI development experiences
Python LangChain LangGraph FastAPI React LLM APIs JupyterLab RAG
View Project Documentation

Machine Learning on the Cloud: End-to-End AI Deployment

Cloud Computing Project | CMU | 2025

  • • Explored feature engineering techniques and trained an XGBoost predictor on Google Vertex AI with discriminative features identified through data inspection
  • • Performed hyperparameter tuning on Vertex AI and deployed the end-to-end ML pipeline on Google App Engine (GAE)
  • • Integrated a Retrieval-Augmented Generation (RAG) system and used prompt engineering to align model behavior with specific use cases
  • • Designed and executed an agentic workflow using LangGraph, enabling modular LLM-based query handling
Google Cloud Platform Vertex AI XGBoost App Engine RAG LangGraph

Commute Ease

Smart Mobility Dashboard (Hackathon Winner)

  • • developed Commute Ease, an innovative, AI-powered solution designed to optimize traffic flow and transform transport management in Kigali
  • • leveraging real-time data to track, analyze, and streamline traffic patterns, enabling data-driven decisions that bring efficiency and sustainability to urban mobility.
  • • elevate user experience and system engagement, we also integrated a cutting-edge Large Language Model (LLM), making the interface more intuitive and empowering for users.
  • • Deployed solution using cloud infrastructure for scalability and reliability
LLM OSM GPS Analytics SQL Cloud Infrastructure

Smart Sorter

Neural Network-Enhanced Recycling Bin

  • • Designing a smart recycling bin using pretrained ResNet-50 models to achieve real-time waste categorization
  • • Incorporate this model into portable devices such as Raspberry Pi for scalable environmental impact.
  • • Implemented containerized deployment for consistent performance across environments
Data Pipeline Power BI Container Deployment IoT

Gender-AI Chatbot

4th Place – Innovation Challenge

  • • Developed inclusive AI assistant for family & gender-based service tracking
  • • Designed UI with built-in reporting for outreach and case study documentation
AI Chatbot UI Design Reporting

CMU Cloud Computing

Academic Projects Series

  • • Getting Started With Cloud Computing: Deployed multi-tier web application
  • • Elasticity: Implemented auto-scaling solutions for variable workloads
  • • Containers: Designed microservices architecture using Docker and Kubernetes
Cloud Computing Docker Kubernetes Microservices

Healthy Transportation to Work Dashboard

ArcGIS Online Dashboard Project

  • • Designed and implemented an interactive ArcGIS Online dashboard to visualize healthy commuting patterns across Allegheny County, PA
  • • Aggregated block group-level transportation data to neighborhood and municipal scales using ArcGIS Pro's geoprocessing tools
  • • Integrated multiple spatial layers to support public health and urban planning decisions
  • • Customized symbology, layout, and interactivity to present key metrics like commute times, walkability, and public transit usage
ArcGIS Online Dashboards GIS Spatial Analysis
View Dashboard

Hospital Accessibility in Rwanda

Graduate GIS Final Project | CMU | May 2025

  • • Conducted spatial analysis of healthcare access across Rwanda using ArcGIS Pro
  • • Created 5 km and 10 km buffer zones to assess population coverage and identify underserved regions
  • • Integrated demographic data with geospatial hospital data to reveal critical disparities in rural healthcare access
  • • Delivered policy-relevant insights and an interactive web map to support targeted infrastructure improvements
ArcGIS Pro Spatial Analysis Buffer Analysis Healthcare
View Web Map

Home Health Services Mapping

Austin, TX Healthcare Analysis | CMU | 2025

  • • Analyzed spatial distribution of home health businesses and healthcare workforce across Austin
  • • Mapped employee counts and sales volumes; integrated demographic layers using Esri's Living Atlas
  • • Created interactive Story Maps visualizing occupational density, business presence, and healthcare accessibility
  • • Applied skills in data extraction, shapefile management, and visualization enhancements
ArcGIS Online Story Maps Data Axle US Census Data
View Story Map

Walking to Work in Pittsburgh

GIS Storytelling Project | CMU | 2025

  • • Developed a web-based StoryMap exploring spatial patterns of walking commuters in Pittsburgh using U.S. Census ACS data
  • • Joined commuting data to geographic census block polygons and analyzed spatial clusters of walk-to-work behavior
  • • Investigated influences such as Pittsburgh's multi-core urban layout, pedestrian bridges, and proximity to universities
  • • Integrated narrative elements, interactive maps, and feature layers into a compelling geographic story
ArcGIS StoryMaps ArcGIS Pro Spatial Join Census Data
View Story Map

Technical Skills

💻

Programming Languages

  • • SQL (MySQL, PostgreSQL)
  • • Python
  • • Java
  • • R
  • • JavaScript
📊

Data Visualization & BI

  • • Power BI
  • • Tableau
  • • Dash
  • • Grafana
  • • Prometheus
⚙️

Data Engineering

  • • Pandas, NumPy
  • • PySpark
  • • Scikit-learn
  • • Airflow
  • • ETL Pipelines
☁️

Cloud & DevOps

  • • Docker
  • • Kubernetes
  • • AWS (EC2, S3, Lambda)
  • • GCP
  • • Azure
🗄️

Data Storage

  • • SQL (MySQL, PostgreSQL)
  • • NoSQL (MongoDB, Redis)
  • • Neo4j
  • • Data Warehousing
🛠️

Development Tools

  • • Git, GitHub
  • • Jupyter
  • • VS Code
  • • Linux
  • • CI/CD Pipelines

Certifications

🧠

Machine Learning

Stanford University (Coursera)

View Certificate
📈

Data Analytics Professional

Google

View Certificate
🔤

NLP Specialization

DeepLearning.AI

View Certificate

Leadership

UR Tech Innovators – Chairman

2019 – 2022

  • Led community impact projects through data-informed decision-making
  • Organized workshops on technology, inclusion, and entrepreneurship during COVID

Get In Touch

Alternatively, you can directly email me at: niygeredi@gmail.com