Daniel Ogenrwot
Phd Research Fellow @Airqo
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WORK HISTORY
Phd Research Fellow @Airqo
Kampala, UG
Summary:Conducting applied research in AI-driven air quality monitoring and cloud-native system design under the AirQo initiative — an African-led platform advancing environmental intelligence through low-cost sensors and data analytics.Key Contributions- Investigating machine learning models for environmental data analytics, focusing on accuracy, scalability, and robustness in low-connectivity regions- Leading the design and evaluation of a cloud-native Software-as-a-Service (SaaS) platform, AirQo Analytics, for near real-time air quality monitoring and visualization- Integrating Testkube, JMeter, and other performance testing tools to evaluate microservices and ensure system reliability- Collaborating with engineers, data scientists, and researchers to improve the data processing pipeline, enabling accurate calibration of sensor data- Co-authoring publications on environmental sensing, data quality, and system optimization in peer-reviewed venues.
EDUCATION
Makerere University
Master of Science - MS, Computer Science
Gulu University
Bachelor of Science (B.S.), Computer Science
University of Nevada-Las Vegas
Doctor of Philosophy - PhD, Computer Science
SKILLS
ABOUT DANIEL OGENRWOT
I\'m a CS PhD student and Graduate Research Assistant in the EVOL Lab at the University of Nevada Las Vegas (UNLV). My research focuses on Empirical Software Engineering, Machine Learning, and AI-assisted software development, particularly in areas such as patch and clone detection, mining software repositories (MSR), and software re-engineering.I\'m currently exploring methods for effect patch integration across structurally diverged software systems and how Large Language Models (LLMs) can enhance software engineering workflows — from automated patch generation to code comprehension and developer productivity. My broader goal is to understand how AI-driven tools can make software development more efficient, reliable, and explainable.Beyond research, I enjoy collaborative and interdisciplinary projects, especially those bridging AI, DevOps, and software analytics. I\'m passionate about mentorship, knowledge sharing, and building inclusive research environments that foster innovation and learning. Let’s connect if you’re interested in discussing AI for software engineering, MSR, or intelligent developer tools.
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