Research
My academic research focuses on applying machine learning and remote sensing technologies to address critical challenges in environmental monitoring, healthcare, and space systems. Below you'll find my current working papers and published conference proceedings.
Research Focus
Exploring the intersection of machine learning theory and applied AI across multiple domains.
Machine Learning
Advancing core ML techniques for scalable and efficient AI systems
AI for Neuroscience
Applying AI to understand and interface with neural systems
AI for Space Systems & EO
Machine learning for spacecraft monitoring and Earth observation applications
Computer Vision-based Calibration of Visual Landing Aids Using Autonomous Drones (PAPI Case Study)
Baimam Boukar JJ, Alice Mugengano, Jonathan Kayizzi, Richard Muhirwa
IEEE Aerospace Conference 2026.
Thermography for Breast Cancer Diagnosis using AI
Baimam Boukar JJ, Peace Bakare, Lucie Niyomutoni
Causal Structure Analysis for Telemetry Anomaly Detection in Spacecraft Systems
Baimam Boukar JJ, Kip Koech
10th TTC International Workshop
Conference Proceedings
Mapping Socioeconomic Air Quality Disparities In Rwanda Using Sentinel-5P TROPOMI Data In Google Earth Engine
Baimam Boukar JJ, Kamikazi Raissa, Bertin Ndahayo, Evelyne Umubyeyi
IEEE MIGARS 2025
Explainable Deep-Learning Based Potentially Hazardous Asteroids Classification Using Graph Neural Networks
Baimam Boukar JJ,
Harvard AstroAI Workshop 2025.
Humidity Inference with Geographic Features and Machine Learning for Enhanced Contrail Prediction for African Airspace
Baimam Boukar JJ, Alice Mugengano, Jonathan Kayizzi
IEEE MIGARS 2025