Aggrey Muhebwa
UN-IPCC scholar | e-GUIDE fellow | Member of DAWG | Ph.D Student
Contact: amuhebwa at umass dot edu.
Job market alert. I am currently on the job market, open to both Applied research scientist and post-doctoral research roles.
About Me
I am a 5th Ph.D student in Electrical and Computer Engineering at the University of Massachusetts Amherst where I am a member of STIMA Lab and honored to be advised by Prof. Jay Taneja.
I am a UN-IPCC scholar, an e-GUIDE fellow and part of DAWG - a consortium of scientists building both physics-based and machine learning algorithms for the upcoming NASA SWOT Mission.
Previously, I completed my masters degree in Electrical and Computer Engineering from Carnegie Mellon University, and a bachelors degree in Computer Engineering from Makerere University.
Research Interests
I leverage machine learning (ML) and satellite data in order to support critical infrastructure (e.g., roads, electricity grid, and water resources) measurement and analysis, sustainable development, and understand the effect of anthropogenic climate change on water resources and the resulting impact on key sectors like clean energy generation, agriculture and transport.
My research is interdisciplinary, sitting at the nexus of Enviromental Engineering, Civil Engineering, Electrical and Computer Engineering, and Computer Science.
For an overview of my published work, see my Google Scholar.
Some of my ongoing projects include:
- Global River Discharge from Pure Satellite Observations: Can we leverage information from data rich regions (e.g., North America) to improve discharge predictions in data sparse regions (e.g., global south) ?
- Fair and Explainable Machine Learning Models in Hydrology: How trustworthy are machine learning models trained and validate using heterogenous data from different geographic regions ?
- Improved Road Quality Prediction from Low Resolution and Sparse Satellite Imagery (Region of Study: Kenya)
Experience
In my previous life, I was water transmission line inspector, a Software Engineer, a Fullstack Engineer, an ML engineer, and Teaching Assistant. If you’d like to know more about my background and education, check out my LinkedIn profile or CV.